doFit_class_Sim.py

#! /usr/bin/env python
import os
import glob
import math
import array
import ROOT
import ntpath

from ROOT import gROOT, gStyle, gSystem, TLatex, TString, TF1,TFile,TLine, TLegend, TH1D,TH2D,THStack,TChain, TCanvas, TMatrixDSym, TMath, TText, TPad, RooFit, RooArgSet, RooArgList, RooArgSet, RooAbsData, RooAbsPdf, RooAddPdf, RooWorkspace, RooExtendPdf,RooCBShape, RooLandau, RooFFTConvPdf, RooGaussian, RooBifurGauss, RooArgusBG, RooDataSet, RooExponential,RooBreitWigner, RooVoigtian, RooNovosibirsk, RooRealVar,RooFormulaVar, RooDataHist, RooHistPdf,RooCategory, RooChebychev, RooSimultaneous, RooGenericPdf,RooConstVar, RooKeysPdf, RooHistPdf, RooEffProd, RooProdPdf, TIter, kTRUE, kFALSE, kGray, kRed, kDashed, kGreen,kAzure, kOrange, kBlack,kBlue,kYellow,kCyan, kMagenta
import subprocess
from subprocess import Popen
from optparse import OptionParser

#from sampleWrapperClass import *
#from trainingClass      import *
#from BoostedWSamples    import * 
#from mvaApplication     import *

import sys

if os.path.isfile('tdrstyle.C'):
   gROOT.ProcessLine('.L tdrstyle.C')
   ROOT.setTDRStyle()
   print "Found tdrstyle.C file, using this style."
#   if os.path.isfile('CMSTopStyle.cc'):
#      gROOT.ProcessLine('.L CMSTopStyle.cc')
#      style = ROOT.CMSTopStyle()
#      style.setupICHEPv1()
#      print "Found CMSTopStyle.cc file, use TOP style if requested in xml file."


ROOT.gSystem.Load("PDFs/HWWLVJRooPdfs_cxx.so")
ROOT.gSystem.Load("PDFs/PdfDiagonalizer_cc.so")
ROOT.gSystem.Load("PDFs/Statistic_cxx.so")

from ROOT import draw_error_band, draw_error_band_extendPdf, draw_error_band_Decor, draw_error_band_shape_Decor, Calc_error_extendPdf, Calc_error, RooErfExpPdf, RooAlpha, RooAlpha4ErfPowPdf, RooAlpha4ErfPow2Pdf, RooAlpha4ErfPowExpPdf, PdfDiagonalizer, RooPowPdf, RooPow2Pdf, RooErfPowExpPdf, RooErfPowPdf, RooErfPow2Pdf, RooQCDPdf, RooUser1Pdf, RooBWRunPdf, ClopperPearsonLimits

############################################################
############################################
#            Job steering                  #
############################################
parser = OptionParser()

parser.add_option('-b', action='store_true', dest='noX', default=False, help='no X11 windows')
parser.add_option('-c', '--channel',action="store",type="string",dest="channel",default="mu")
#parser.add_option('-p', '--psmodel',action="store",type="string",dest="psmodel",default="pythia")
parser.add_option('-p', '--psmodel',action="store",type="string",dest="psmodel",default="herwig")
parser.add_option('-s','--simple', action='store_true', dest='simple', default=True, help='pre-limit in simple mode')
parser.add_option('-m','--multi', action='store_true', dest='multi', default=False, help='pre-limit in multi mode')
parser.add_option('--fitwtagger', action='store_true', dest='fitwtagger', default=False, help='fit wtagger jet in ttbar control sample')
parser.add_option('--fitwtaggersim', action='store_true', dest='fitwtaggersim', default=False, help='fit wtagger jet in ttbar control sample with mu and el samples simultaneously')
parser.add_option('--check', action='store_true', dest='check', default=False, help='check the workspace for limit setting')
parser.add_option('--control', action='store_true', dest='control', default=False, help='control plot')
parser.add_option('--fitsignal', action='store_true', dest='fitsignal', default=False, help='fit signal')
parser.add_option('--cprime', action="store",type="int",dest="cprime",default=10)
parser.add_option('--BRnew', action="store",type="int",dest="BRnew",default=0)


(options, args) = parser.parse_args()
############################################################

class doFit_wj_and_wlvj:
    def __init__(self, in_channel="mu",in_higgs_sample="ggH600", in_mlvj_signal_region_min=500, in_mlvj_signal_region_max=700, in_mj_min=30, in_mj_max=140, in_mlvj_min=400., in_mlvj_max=1400., fit_model="ErfExp_v1", fit_model_alter="ErfPow_v1", input_workspace=None):
        print "Begin to fit"

        RooAbsPdf.defaultIntegratorConfig().setEpsRel(1e-9) ;
        RooAbsPdf.defaultIntegratorConfig().setEpsAbs(1e-9) ;

        self.channel=in_channel;#el or muon
        self.higgs_sample=in_higgs_sample;
        if in_higgs_sample=="ggH600": self.vbfhiggs_sample="vbfH600";
        if in_higgs_sample=="ggH700": self.vbfhiggs_sample="vbfH700";
        if in_higgs_sample=="ggH800": self.vbfhiggs_sample="vbfH800";
        if in_higgs_sample=="ggH900": self.vbfhiggs_sample="vbfH900";
        if in_higgs_sample=="ggH1000":self.vbfhiggs_sample="vbfH1000";
        if in_higgs_sample=="ggH1500":self.vbfhiggs_sample="vbfH1500";
        if in_higgs_sample=="ggH2000":self.vbfhiggs_sample="vbfH2000";

        self.BinWidth_mlvj=50.;
        self.BinWidth_mj=5;
        nbins_mlvj=int((in_mlvj_max-in_mlvj_min)/self.BinWidth_mlvj);
        in_mlvj_max=in_mlvj_min+nbins_mlvj*self.BinWidth_mlvj;
        nbins_mj=int((in_mj_max-in_mj_min)/self.BinWidth_mj);
        in_mj_max=in_mj_min+nbins_mj*self.BinWidth_mj;

        rrv_mass_j  = RooRealVar("rrv_mass_j","mass(j)",(in_mj_min+in_mj_max)/2.,in_mj_min,in_mj_max,"GeV/c^{2}");
        rrv_mass_j.setBins(nbins_mj);
        rrv_mass_lvj= RooRealVar("rrv_mass_lvj","mass(lvj)",(in_mlvj_min+in_mlvj_max)/2.,in_mlvj_min,in_mlvj_max,"GeV/c^{2}");
        rrv_mass_lvj.setBins(nbins_mlvj);

        if input_workspace is None:
            self.workspace4fit_ = RooWorkspace("workspace4fit_","workspace4fit_");
        else:
            self.workspace4fit_ = input_workspace;
        getattr(self.workspace4fit_,"import")(rrv_mass_j);
        getattr(self.workspace4fit_,"import")(rrv_mass_lvj);

        #prepare workspace for unbin-Limit
        self.workspace4limit_ = RooWorkspace("workspace4limit_","workspace4limit_");

        self.mj_sideband_lo_min=in_mj_min;
        self.mj_sideband_lo_max=65;
        self.mj_signal_min=65;
        self.mj_signal_max=105;
        self.mj_sideband_hi_min=105;
        self.mj_sideband_hi_max=in_mj_max;
        # test
        #self.mj_sideband_lo_min=30;
        #self.mj_sideband_lo_max=52;
        #self.mj_signal_min=52;
        #self.mj_signal_max=67;
        #self.mj_sideband_hi_min=100;
        #self.mj_sideband_hi_max=125;
        rrv_mass_j.setRange("sb_lo",self.mj_sideband_lo_min,self.mj_sideband_lo_max);
        rrv_mass_j.setRange("signal_region",self.mj_signal_min,self.mj_signal_max); 
        rrv_mass_j.setRange("sb_hi",self.mj_sideband_hi_min,self.mj_sideband_hi_max);
        rrv_mass_j.setRange("sblo_to_sbhi",self.mj_sideband_lo_min,self.mj_sideband_hi_max);
        rrv_mass_j.setRange("controlsample_fitting_range",40,130);

        self.mlvj_signal_min=in_mlvj_signal_region_min
        self.mlvj_signal_max=in_mlvj_signal_region_max
        rrv_mass_lvj.setRange("signal_region",self.mlvj_signal_min,self.mlvj_signal_max); 

        #prepare the data and mc files
        if options.fitwtagger or options.fitwtaggersim:
            #self.file_Directory="trainingtrees_19_Jan24/trainingtrees_%s/"%(self.channel);
            self.file_Directory="trainingtrees_%s/"%(self.channel);
        else: 
            self.file_Directory="trainingtrees_%s/"%(self.channel);

        self.PS_model= options.psmodel
        #self.PS_model="pythia"; #self.PS_model="herwig"
 
        #self.file_data=("ofile_data_sub.root");#keep blind!!!!
        self.file_data=("ofile_data.root");#keep blind!!!!
        #self.file_data=("ofile_pseudodata.root");#keep blind!!!!
        #self.file_data=("ofile_pseudodata_with_ggH600.root");#keep blind!!!!
        #self.file_data=("ofile_pseudodata_with_ggH700.root");#keep blind!!!!
        #self.file_data=("ofile_pseudodata_with_ggH800.root");#keep blind!!!!
        #self.file_data=("ofile_pseudodata_with_ggH900.root");#keep blind!!!!
        #self.file_data=("ofile_pseudodata_with_ggH1000.root");#keep blind!!!!
        self.file_pseudodata=("ofile_pseudodata.root");#fake data
        self.file_ggH=("ofile_%s.root"%(self.higgs_sample));
        self.file_vbfH=("ofile_%s.root"%(self.vbfhiggs_sample));
        #WJets0 is the default PS model, WJets1 is the alternative PS model
        if self.PS_model=="pythia":
            self.file_WJets0_mc=("ofile_WJets_Pythia.root");
            self.file_WJets1_mc=("ofile_WJets_Herwig.root");
        else:
            self.file_WJets0_mc=("ofile_WJets_Herwig.root");
            self.file_WJets1_mc=("ofile_WJets_Pythia.root");
        self.file_VV_mc=("ofile_VV.root");# WW+WZ 
        self.file_TTbar_mc=("ofile_TTbar.root");
        self.file_TTbar_matchDn_mc=("ofile_TTbar_matchDn.root");
        self.file_TTbar_matchUp_mc=("ofile_TTbar_matchUp.root");
        self.file_TTbar_scaleDn_mc=("ofile_TTbar_scaleDn.root");
        self.file_TTbar_scaleUp_mc=("ofile_TTbar_scaleUp.root");
        #self.file_TTbar_Powheg_mc=("ofile_TTbar_Powheg.root");
        self.file_TTbar_MG_mc=("ofile_TTbar_MG.root");
        self.file_STop_mc =("ofile_STop.root");#single Top
        
        #result files: The event number, parameters and error write into a txt file. The dataset and pdfs write into a root file
        if not os.path.isdir("cards_%s"%(self.channel)): os.system("mkdir cards_%s"%(self.channel));
        self.rlt_DIR="cards_%s/"%(self.channel)

        self.file_rlt_txt           = self.rlt_DIR+"other_hwwlvj_%s_%s_%02d_%02d.txt"%(self.higgs_sample,self.channel,options.cprime,options.BRnew)
        self.file_rlt_root          = self.rlt_DIR+"hwwlvj_%s_%s_%02d_%02d_workspace.root"%(self.higgs_sample,self.channel,options.cprime,options.BRnew)
        self.file_datacard_unbin    = self.rlt_DIR+"hwwlvj_%s_%s_%02d_%02d_unbin.txt"%(self.higgs_sample,self.channel,options.cprime,options.BRnew)
        self.file_datacard_counting = self.rlt_DIR+"hwwlvj_%s_%s_%02d_%02d_counting.txt"%(self.higgs_sample,self.channel,options.cprime,options.BRnew)

        
        self.file_out=open(self.file_rlt_txt,"w");
        self.file_out.write("Welcome:\n");
        self.file_out.close()
        self.file_out=open(self.file_rlt_txt,"a+");

        self.higgs_xs_scale=1.0; #higgs XS scale
        
        self.color_palet={ #color palet
            #'WJets' : style.WJetsColor,
            #'VV'    : style.DibosonsColor,
            #'TTbar' : style.TtbarColor,
            #'STop'  : style.SingleTopColor,
            'data'  : kBlack,
            'WJets' : kRed,
            'VV'    : kAzure+8,
            'TTbar' : kGreen,
            'STop'  : kYellow,
            'Signal': kBlack,
            'vbfSignal': kGray+2,
            'Uncertainty' : kBlack,
            'Other_Backgrounds'  : kBlue
        }

        #self.wtagger_label="tight";#50%
        self.wtagger_label="medium";#75%
        #self.wtagger_label="loose";#90%
        #self.wtagger_label="nocut";#nocut
        if self.wtagger_label=="tight":
            if self.channel=="el":self.wtagger_cut=0.43  ;
            if self.channel=="mu":self.wtagger_cut=0.43  ;
        if self.wtagger_label=="medium":
            if self.channel=="el":self.wtagger_cut=0.55  ;
            if self.channel=="mu":self.wtagger_cut=0.55  ;
        if self.wtagger_label=="loose":
            if self.channel=="el":self.wtagger_cut=0.66  ;
            if self.channel=="mu":self.wtagger_cut=0.65  ;
        if self.wtagger_label=="nocut": self.wtagger_cut=10000;

        #medium wtagger_eff reweight between data and mc
        if self.channel=="mu":
            self.rrv_wtagger_eff_reweight_forTop=RooRealVar("rrv_wtagger_eff_reweight_forTop","rrv_wtagger_eff_reweight_forTop",0.96); self.rrv_wtagger_eff_reweight_forTop.setError(0.06*self.rrv_wtagger_eff_reweight_forTop.getVal());
            self.rrv_wtagger_eff_reweight_forV=RooRealVar("rrv_wtagger_eff_reweight_forV","rrv_wtagger_eff_reweight_forV",1.0); self.rrv_wtagger_eff_reweight_forV.setError(0.075*self.rrv_wtagger_eff_reweight_forV.getVal());
        if self.channel=="el":
            self.rrv_wtagger_eff_reweight_forTop=RooRealVar("rrv_wtagger_eff_reweight_forTop","rrv_wtagger_eff_reweight_forTop",0.92); self.rrv_wtagger_eff_reweight_forTop.setError(0.06*self.rrv_wtagger_eff_reweight_forTop.getVal());
            self.rrv_wtagger_eff_reweight_forV=RooRealVar("rrv_wtagger_eff_reweight_forV","rrv_wtagger_eff_reweight_forV",1.0); self.rrv_wtagger_eff_reweight_forV.setError(0.075*self.rrv_wtagger_eff_reweight_forV.getVal());
        print "wtagger efficiency correction for Top sample: %s +/- %s"%(self.rrv_wtagger_eff_reweight_forTop.getVal(), self.rrv_wtagger_eff_reweight_forTop.getError());
        print "wtagger efficiency correction for V   sample: %s +/- %s"%(self.rrv_wtagger_eff_reweight_forV.getVal(), self.rrv_wtagger_eff_reweight_forV.getError());


        #PU study: 0-11,11-15,15-100
        self.nPV_min=  0;
        self.nPV_max= 300;
        self.vpt_cut= 200;
		#met cut:el 70; mu: 50
        self.pfMET_cut= 50;
        self.lpt_cut = 30;
        if self.channel=="el":
            self.pfMET_cut= 70; 
            self.lpt_cut = 35;        
        #deltaPhi_METj cut
        self.deltaPhi_METj_cut =2.0;

        self.file_ttbar_control_txt = "ttbar_control_%s_%s_wtaggercut%s.txt"%(self.higgs_sample,self.channel,self.wtagger_label);
        self.file_out_ttbar_control=open(self.file_ttbar_control_txt,"w");

        self.MODEL_4_mlvj=fit_model;
        self.MODEL_4_mlvj_alter=fit_model_alter;

        # parameters of data-driven method to get the WJets background event number.
        self.number_WJets_insideband=-1;
        self.datadriven_alpha_WJets_unbin=-1;
        self.datadriven_alpha_WJets_counting=-1;

        #uncertainty for datacard
        self.lumi_uncertainty=0.044;  
        #self.XS_TTbar_uncertainty=0.063;# from AN-12-368 table8 
        #self.XS_STop_uncertainty =0.05 ;# from AN-12-368 table8 
        #self.XS_VV_uncertainty   =0.10 ;# from AN-12-368 table8 
        self.XS_STop_uncertainty =0.30 ; 
        self.XS_VV_uncertainty   =0.30 ; 
        self.QCDscale_ggH    =0.10; self.QCDscale_vbfH    =0.01;
        self.pdf_gg           =0.0; self.pdf_vbf          =0.0;
        self.hwwlnJ_pdfAcc_gg=0.03; self.hwwlnJ_pdfAcc_vbf=0.01;
        # from twiki https://twiki.cern.ch/twiki/bin/view/LHCPhysics/CERNYellowReportPageAt8TeV,  
        if self.higgs_sample=="ggH600": 
            self.QCDscale_ggH =0.059;   self.QCDscale_vbfH=0.007
            self.pdf_gg       =0.095;   self.pdf_vbf      =0.036
            self.hwwlnJ_pdfAcc_gg=0.036;self.hwwlnJ_pdfAcc_vbf=0.007
        if self.higgs_sample=="ggH700": 
            self.QCDscale_ggH =0.060;   self.QCDscale_vbfH=0.008;
            self.pdf_gg       =0.101;   self.pdf_vbf      =0.042
            self.hwwlnJ_pdfAcc_gg=0.038;self.hwwlnJ_pdfAcc_vbf=0.008
        if self.higgs_sample=="ggH800": 
            self.QCDscale_ggH =0.061;   self.QCDscale_vbfH=0.010;
            self.pdf_gg       =0.106;   self.pdf_vbf      =0.047;
            self.hwwlnJ_pdfAcc_gg=0.040;self.hwwlnJ_pdfAcc_vbf=0.009
        if self.higgs_sample=="ggH900": 
            self.QCDscale_ggH =0.063;   self.QCDscale_vbfH=0.012
            self.pdf_gg       =0.111;   self.pdf_vbf      =0.053
            self.hwwlnJ_pdfAcc_gg=0.042;self.hwwlnJ_pdfAcc_vbf=0.010
        if self.higgs_sample=="ggH1000": 
            self.QCDscale_ggH =0.065;   self.QCDscale_vbfH=0.013;
            self.pdf_gg       =0.121;   self.pdf_vbf      =0.059; 
            self.hwwlnJ_pdfAcc_gg=0.046;self.hwwlnJ_pdfAcc_vbf=0.011
        self.interference_ggH_uncertainty=0.1;
        self.interference_vbfH_uncertainty=0.5;
        #normlization uncertainty from jet_mass
        self.WJets_normlization_uncertainty_from_jet_mass=0.;
        self.VV_normlization_uncertainty_from_jet_mass=0.;
        self.STop_normlization_uncertainty_from_jet_mass=0.;
        self.TTbar_normlization_uncertainty_from_jet_mass=0.;
        #el and mu trigger and eff uncertainty, AN2012_368_v5 12.3
        self.lep_trigger_uncertainty=0.01;
        self.lep_eff_uncertainty=0.02;

        #b tag scale uncertainty
        self.btag_scale=0.98;
        self.btag_scale_uncertainty=0.025;


        # shape parameter uncertainty
        self.FloatingParams=RooArgList("floatpara_list");

    ##################### ---------------------------------------------------
    def make_Pdf(self, label, in_model_name, mass_spectrum="_mj", ConstraintsList=[]):
        if TString(mass_spectrum).Contains("_mj"): rrv_x = self.workspace4fit_.var("rrv_mass_j"); 
        if TString(mass_spectrum).Contains("_mlvj"): rrv_x = self.workspace4fit_.var("rrv_mass_lvj"); 
        
        if in_model_name == "Voig":
            rrv_mean_voig=RooRealVar("rrv_mean_voig"+label+"_"+self.channel,"rrv_mean_voig"+label+"_"+self.channel,84,78,88);# W mass: 80.385
            rrv_width_voig=RooRealVar("rrv_width_voig"+label+"_"+self.channel,"rrv_width_voig"+label+"_"+self.channel,7.,1,40);
            rrv_sigma_voig=RooRealVar("rrv_sigma_voig"+label+"_"+self.channel,"rrv_sigma_voig"+label+"_"+self.channel,5,0.01,20);
            model_pdf = RooVoigtian("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_voig,rrv_width_voig,rrv_sigma_voig);

        if in_model_name == "Voig_v1":
            rrv_mean_voig=RooRealVar("rrv_mean_voig"+label+"_"+self.channel,"rrv_mean_voig"+label+"_"+self.channel,650,550,1200);# Higgs mass 600-1000
            rrv_width_voig=RooRealVar("rrv_width_voig"+label+"_"+self.channel,"rrv_width_voig"+label+"_"+self.channel,100.,10,600);
            rrv_sigma_voig=RooRealVar("rrv_sigma_voig"+label+"_"+self.channel,"rrv_sigma_voig"+label+"_"+self.channel,200,10,400);
            model_pdf = RooVoigtian("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_voig,rrv_width_voig,rrv_sigma_voig);
    
        if in_model_name == "BW": # FFT: BreitWigner*CBShape
            rrv_mean_BW=RooRealVar("rrv_mean_BW"+label+"_"+self.channel,"rrv_mean_BW"+label+"_"+self.channel,84,78, 88);
            rrv_width_BW=RooRealVar("rrv_width_BW"+label+"_"+self.channel,"rrv_width_BW"+label+"_"+self.channel,20,1,40);
            model_pdf = RooBreitWigner("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_BW,rrv_width_BW);

        if in_model_name == "BW_v1": # FFT: BreitWigner*CBShape
            rrv_mean_BW=RooRealVar("rrv_mean_BW"+label+"_"+self.channel,"rrv_mean_BW"+label+"_"+self.channel,900,400, 1200);
            rrv_width_BW=RooRealVar("rrv_width_BW"+label+"_"+self.channel,"rrv_width_BW"+label+"_"+self.channel,400,200,800);
            model_pdf = RooBreitWigner("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_BW,rrv_width_BW);

        if in_model_name == "BWRUN":
            if label=="_ggH600_signal_region" or label=="_ggH600_sb_lo":
                rrv_mean_BWRUN = RooRealVar("rrv_mean_BWRUN"+label+"_"+self.channel,"rrv_mean_BWRUN"+label+"_"+self.channel,600,550,650);
                rrv_width_BWRUN= RooRealVar("rrv_width_BWRUN"+label+"_"+self.channel,"rrv_width_BWRUN"+label+"_"+self.channel,60,50,70);
            if label=="_ggH700_signal_region" or label=="_ggH700_sb_lo":
                rrv_mean_BWRUN = RooRealVar("rrv_mean_BWRUN"+label+"_"+self.channel,"rrv_mean_BWRUN"+label+"_"+self.channel,700,650,750);
                rrv_width_BWRUN= RooRealVar("rrv_width_BWRUN"+label+"_"+self.channel,"rrv_width_BWRUN"+label+"_"+self.channel,100,80,120);
            if label=="_ggH800_signal_region" or label=="_ggH800_sb_lo": 
                rrv_mean_BWRUN = RooRealVar("rrv_mean_BWRUN"+label+"_"+self.channel,"rrv_mean_BWRUN"+label+"_"+self.channel,800,750,850);
                rrv_width_BWRUN= RooRealVar("rrv_width_BWRUN"+label+"_"+self.channel,"rrv_width_BWRUN"+label+"_"+self.channel,150,100,180);
            if label=="_ggH900_signal_region" or label=="_ggH900_sb_lo": 
                rrv_mean_BWRUN = RooRealVar("rrv_mean_BWRUN"+label+"_"+self.channel,"rrv_mean_BWRUN"+label+"_"+self.channel,900,850,990);
                rrv_width_BWRUN= RooRealVar("rrv_width_BWRUN"+label+"_"+self.channel,"rrv_width_BWRUN"+label+"_"+self.channel,200,100,260);
            if label=="_ggH1000_signal_region" or label=="_ggH1000_sb_lo":
                rrv_mean_BWRUN = RooRealVar("rrv_mean_BWRUN"+label+"_"+self.channel,"rrv_mean_BWRUN"+label+"_"+self.channel,1000,950,1050);
                rrv_width_BWRUN= RooRealVar("rrv_width_BWRUN"+label+"_"+self.channel,"rrv_width_BWRUN"+label+"_"+self.channel,200,100,370); 
            #rrv_mean_BWRUN = RooRealVar("rrv_mean_BWRUN"+label+"_"+self.channel,"rrv_mean_BWRUN"+label+"_"+self.channel,800,400,1200);
            #rrv_width_BWRUN= RooRealVar("rrv_width_BWRUN"+label+"_"+self.channel,"rrv_width_BWRUN"+label+"_"+self.channel,200,30,500);
            bwrun = RooBWRunPdf("bwrun"+label+"_"+self.channel+mass_spectrum,"bwrun"+label+"_"+self.channel+mass_spectrum,rrv_x, rrv_mean_BWRUN, rrv_width_BWRUN);

            rrv_mean_cb = RooRealVar("rrv_mean_cb"+label+"_"+self.channel,"rrv_mean_cb"+label+"_"+self.channel,0);
            rrv_sigma_cb = RooRealVar("rrv_sigma_cb"+label+"_"+self.channel,"rrv_sigma_cb"+label+"_"+self.channel,50,10,300);
            rrv_alpha_cb = RooRealVar("rrv_alpha_cb"+label+"_"+self.channel,"rrv_alpha_cb"+label+"_"+self.channel,-3,-20,-1);
            rrv_n_cb = RooRealVar("rrv_n_cb"+label+"_"+self.channel,"rrv_n_cb"+label+"_"+self.channel,5,1,9);
            #cbshape = RooCBShape("cbshape"+label+"_"+self.channel,"cbshape"+label+"_"+self.channel, rrv_x,rrv_mean_cb,rrv_sigma_cb,rrv_alpha_cb,rrv_n_cb);
            cbshape = RooGaussian("cbshape"+label+"_"+self.channel,"cbshape"+label+"_"+self.channel, rrv_x,rrv_mean_cb,rrv_sigma_cb);
            fft = RooFFTConvPdf("fft"+label+"_"+self.channel+mass_spectrum,"fft"+label+"_"+self.channel+mass_spectrum, rrv_x, bwrun, cbshape);

            #rrv_mean_novo = RooRealVar("rrv_mean_novo"+label+"_"+self.channel,"rrv_mean_novo"+label+"_"+self.channel,0);
            #rrv_sigma_novo = RooRealVar("rrv_sigma_novo"+label+"_"+self.channel,"rrv_sigma_novo"+label+"_"+self.channel,40,10,100);
            #rrv_alpha_novo = RooRealVar("rrv_alpha_novo"+label+"_"+self.channel,"rrv_alpha_novo"+label+"_"+self.channel,0,-0.5,0.5);
            #novo = RooNovosibirsk("novo"+label+"_"+self.channel,"novo"+label+"_"+self.channel, rrv_x,rrv_mean_novo,rrv_sigma_novo,rrv_alpha_novo);
            ##fft = RooFFTConvPdf("fft"+label+"_"+self.channel+mass_spectrum,"fft"+label+"_"+self.channel+mass_spectrum, rrv_x, bwrun, novo);
            #model_pdf = RooFFTConvPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x, bwrun, novo);

            rrv_offset_erf = RooRealVar("rrv_offset_erf"+label+"_"+self.channel,"rrv_offset_erf"+label+"_"+self.channel,450)#,350,550);
            rrv_width_erf = RooRealVar("rrv_width_erf"+label+"_"+self.channel,"rrv_width_erf"+label+"_"+self.channel,50)#,10,250);
            erf =  RooGenericPdf("erf"+label+"_"+self.channel+mass_spectrum,"erf"+label+"_"+self.channel+mass_spectrum, "(1.+TMath::Erf((%s-%s)/%s))/2."%( rrv_x.GetName(),rrv_offset_erf.GetName(), rrv_width_erf.GetName()), RooArgList(rrv_x,rrv_offset_erf,rrv_width_erf) )

            model_pdf = RooProdPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, fft, erf );
 
        if in_model_name == "2Voig":
            rrv_mean_voig=RooRealVar("rrv_mean_voig"+label+"_"+self.channel,"rrv_mean_voig"+label+"_"+self.channel,84,78,88);#W mass 80.385
            rrv_shift_2Voig=RooRealVar("rrv_shift_2Voig"+label+"_"+self.channel,"rrv_shift_2Voig"+label+"_"+self.channel,10.8026)   # Z mass: 91.1876;  shift=91.1876-80.385=10.8026
            rrv_mean_shifted= RooFormulaVar("rrv_mean_voig2"+label+"_"+self.channel,"@0+@1",RooArgList(rrv_mean_voig,rrv_shift_2Voig));
            rrv_width_voig=RooRealVar("rrv_width_voig"+label+"_"+self.channel,"rrv_width_voig"+label+"_"+self.channel,16.,6,26);
            #rrv_sigma_voig=RooRealVar("rrv_sigma_voig"+label+"_"+self.channel,"rrv_sigma_voig"+label+"_"+self.channel,2,0.5,5);
            rrv_sigma_voig=RooRealVar("rrv_sigma_voig"+label+"_"+self.channel,"rrv_sigma_voig"+label+"_"+self.channel,0.);
            rrv_frac=RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,0.8,0.5,1.);
            model_voig1 = RooVoigtian("model_voig1"+label+"_"+self.channel+mass_spectrum,"model_voig1"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_voig,rrv_width_voig,rrv_sigma_voig);
            model_voig2 = RooVoigtian("model_voig2"+label+"_"+self.channel+mass_spectrum,"model_voig2"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_shifted,rrv_width_voig,rrv_sigma_voig);
            model_pdf = RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, RooArgList(model_voig1,model_voig2), RooArgList(rrv_frac));
    
        if in_model_name == "Gaus":
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,84,78,88);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,7,1,15);
            model_pdf = RooGaussian("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);

        if in_model_name == "Gaus_v1":
            if label=="_ggH600_signal_region" or label=="_ggH600_sb_lo":
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,580,550,620);
                rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,65,40,80);
            if label=="_ggH700_signal_region" or label=="_ggH700_sb_lo":
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,700,650,750);
                rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,100,40,150);
            if label=="_ggH800_signal_region" or label=="_ggH800_sb_lo": 
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,800,750,850);
                rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,130,120,140);
            if label=="_ggH900_signal_region" or label=="_ggH900_sb_lo": 
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,900,850,900);
                rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,160,140,180);
            if label=="_ggH1000_signal_region" or label=="_ggH1000_sb_lo":
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,920,900,1000);
                rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,200,100,300);
            model_pdf = RooGaussian("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
 
        if in_model_name == "BifurGaus_v1":
            if label=="_ggH600_signal_region":
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,600,550,650);
                rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,67,40,80);
                rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,67,40,80);
            if label=="_ggH700_signal_region":
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,700,650,750);
                rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,100,40,150);
                rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,100,40,150);
            if label=="_ggH800_signal_region": 
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,800,750,850);
                rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,130,120,140);
                rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,130,120,140);
            if label=="_ggH900_signal_region": 
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,900,850,900);
                rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,160,140,180);
                rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,160,140,180);
            if label=="_ggH1000_signal_region":
                rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,920,900,1000);
                rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,200,100,300);
                rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,200,100,300);
            model_pdf = RooBifurGauss("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_gaus,rrv_sigma1_gaus,rrv_sigma2_gaus);
    
        if in_model_name == "CB":
            rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,84,78,88);
            rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,7,4,10);
            rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,-2,-4,-0.5);
            rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,2,0.,4);
            model_pdf = RooCBShape("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_CB,rrv_sigma_CB,rrv_alpha_CB,rrv_n_CB);

        if in_model_name == "SCB_v1":
            rrv_mean_SCB=RooRealVar("rrv_mean_SCB"+label+"_"+self.channel,"rrv_mean_SCB"+label+"_"+self.channel,800,550,1000);
            rrv_sigma_SCB=RooRealVar("rrv_sigma_SCB"+label+"_"+self.channel,"rrv_sigma_SCB"+label+"_"+self.channel,70,40,300);
            rrv_alpha1_SCB=RooRealVar("rrv_alpha1_SCB"+label+"_"+self.channel,"rrv_alpha1_SCB"+label+"_"+self.channel,-2,-4,-0.5);
            rrv_alpha2_SCB=RooRealVar("rrv_alpha2_SCB"+label+"_"+self.channel,"rrv_alpha2_SCB"+label+"_"+self.channel,2,0.5,4);
            rrv_n1_SCB=RooRealVar("rrv_n1_SCB"+label+"_"+self.channel,"rrv_n1_SCB"+label+"_"+self.channel,2,0.,4);
            rrv_n2_SCB=RooRealVar("rrv_n2_SCB"+label+"_"+self.channel,"rrv_n2_SCB"+label+"_"+self.channel,2,0.,4);
            frac=RooRealVar("rrv_frac_SSCB"+label+"_"+self.channel,"rrv_frac_SSCB"+label+"_"+self.channel,0.5)
            scb1 = RooCBShape("model_pdf_scb1"+label+"_"+self.channel+mass_spectrum,"model_pdf_scb1"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_SCB,rrv_sigma_SCB,rrv_alpha1_SCB,rrv_n1_SCB);
            scb2 = RooCBShape("model_pdf_scb2"+label+"_"+self.channel+mass_spectrum,"model_pdf_scb2"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_SCB,rrv_sigma_SCB,rrv_alpha2_SCB,rrv_n2_SCB);
            model_pdf=RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(scb1,scb2),RooArgList(frac))

        if in_model_name == "CB_v1":
            label_tstring=TString(label);
            if label_tstring.Contains("H600"): 
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,600,580,620);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,67,40,80);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,-1,-2,-0.5);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,20.,10,80 );
            elif label_tstring.Contains("H700"):
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,700,650,750);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,100,40,150);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,-1,-3,-0.1);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,20.,10,40);
            elif label_tstring.Contains("ggH800"): 
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,780,700,850);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,140,120,160);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,-1,-4,0);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,5  , 2, 7);
            elif label_tstring.Contains("vbfH800"): 
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,800,750,850);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,140,120,160);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,-1,-4,0);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,5  , 2, 7);
            elif label_tstring.Contains("ggH900"):
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,880,820,950);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,170,140,200);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,1,0,4);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel, 2., 0.5,5);
            elif label_tstring.Contains("vbfH900"):
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,900,880,920);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,170,140,200);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,1);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel, 2., 0.5,5);
            elif label_tstring.Contains("ggH1000"): 
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,920,800,1150);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,200,100,300);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,1,0.1,3);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,2.,0.5,4);
            elif label_tstring.Contains("vbfH1000"): 
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,1000,980,1150);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,200,100,300);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,0.72);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,2.,0.5,4);
            else:
                rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,700,550,1000);
                rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,100,40 ,300);
                rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,0,-5,5);
                rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,20.,10,40);

            model_pdf = RooCBShape("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_mean_CB,rrv_sigma_CB,rrv_alpha_CB,rrv_n_CB);
        if in_model_name == "ArgusBW_v1":
            label_tstring=TString(label);
            if label_tstring.Contains("ggH1000"): 
                #rrv_mean_BW=RooRealVar("rrv_mean_BW"+label+"_"+self.channel,"rrv_mean_BW"+label+"_"+self.channel,1000,800,1100);
                rrv_width_BW=RooRealVar("rrv_width_BW"+label+"_"+self.channel,"rrv_width_BW"+label+"_"+self.channel,100,50,600);
                rrv_m0_Argus=RooRealVar("rrv_m0_Argus"+label+"_"+self.channel,"rrv_m0_Argus"+label+"_"+self.channel, 950         );
                rrv_c_Argus=RooRealVar("rrv_c_Argus"+label+"_"+self.channel,"rrv_c_Argus"+label+"_"+self.channel,-1,-2,-1e-1);
                rrv_frac=RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,0.5,0.0,1.);
            else:
                #rrv_mean_BW=RooRealVar("rrv_mean_BW"+label+"_"+self.channel,"rrv_mean_BW"+label+"_"+self.channel,900,800,1000);
                rrv_width_BW=RooRealVar("rrv_width_BW"+label+"_"+self.channel,"rrv_width_BW"+label+"_"+self.channel,200,50,400);
                rrv_m0_Argus=RooRealVar("rrv_m0_Argus"+label+"_"+self.channel,"rrv_m0_Argus"+label+"_"+self.channel,1000);
                rrv_c_Argus=RooRealVar("rrv_c_Argus"+label+"_"+self.channel,"rrv_c_Argus"+label+"_"+self.channel,-1,-2,0.1);
                rrv_frac=RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,0.5,0.0,1.);
            #bw = RooBreitWigner("bw"+label+"_"+self.channel,"bw"+label+"_"+self.channel, rrv_x,rrv_mean_BW,rrv_width_BW);
            bw = RooBreitWigner("bw"+label+"_"+self.channel,"bw"+label+"_"+self.channel, rrv_x,rrv_m0_Argus,rrv_width_BW);
            argus=RooArgusBG("argus"+label+"_"+self.channel,"argus"+label+"_"+self.channel, rrv_x, rrv_m0_Argus,rrv_c_Argus);
            model_pdf = RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, RooArgList(bw,argus), RooArgList(rrv_frac));
    
        if in_model_name == "CBBW": # FFT: BreitWigner*CBShape
            rrv_mean_CB=RooRealVar("rrv_mean_CB"+label+"_"+self.channel,"rrv_mean_CB"+label+"_"+self.channel,84.0,78,88);
            rrv_sigma_CB=RooRealVar("rrv_sigma_CB"+label+"_"+self.channel,"rrv_sigma_CB"+label+"_"+self.channel,7,4,10);
            rrv_alpha_CB=RooRealVar("rrv_alpha_CB"+label+"_"+self.channel,"rrv_alpha_CB"+label+"_"+self.channel,-2,-4,-1);
            rrv_n_CB=RooRealVar("rrv_n_CB"+label+"_"+self.channel,"rrv_n_CB"+label+"_"+self.channel,0.5,0.,2);
            rrv_mean_BW=RooRealVar("rrv_mean_BW"+label+"_"+self.channel,"rrv_mean_BW"+label+"_"+self.channel,0);
            rrv_width_BW=RooRealVar("rrv_width_BW"+label+"_"+self.channel,"rrv_width_BW"+label+"_"+self.channel,10,5,20);
            cbshape = RooCBShape("cbshape"+label+"_"+self.channel,"cbshape"+label+"_"+self.channel, rrv_x,rrv_mean_CB,rrv_sigma_CB,rrv_alpha_CB,rrv_n_CB);
            bw = RooBreitWigner("bw"+label+"_"+self.channel,"bw"+label+"_"+self.channel, rrv_x,rrv_mean_BW,rrv_width_BW);
            model_pdf = RooFFTConvPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x, cbshape, bw);

        if in_model_name == "LDGaus": # FFT: Landau*Gaus
            rrv_mean_landau=RooRealVar("rrv_mean_landau"+label+"_"+self.channel,"rrv_mean_landau"+label+"_"+self.channel,84.0,78,88);
            rrv_sigma_landau=RooRealVar("rrv_sigma_landau"+label+"_"+self.channel,"rrv_sigma_landau"+label+"_"+self.channel,7,4,10);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,0);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,16,10,20);
            landau = RooLandau("landau"+label+"_"+self.channel,"landau"+label+"_"+self.channel, rrv_x,rrv_mean_landau,rrv_sigma_landau);
            gaus = RooBreitWigner("gaus"+label+"_"+self.channel,"gaus"+label+"_"+self.channel, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
            model_pdf = RooFFTConvPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x, landau, gaus);

        if in_model_name == "Exp"  or in_model_name == "Exp_sr":
            rrv_c_Exp = RooRealVar("rrv_c_Exp"+label+"_"+self.channel,"rrv_c_Exp"+label+"_"+self.channel,-0.05,-0.1,0.);
            model_pdf = ROOT.RooExponential("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_Exp);

        if in_model_name == "ErfExp" :
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-0.1,-1e-4);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,60.,30.,120);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.)#,10, 60.);
            model_pdf = ROOT.RooErfExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            #model_pdf = RooGenericPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, "TMath::Exp(%s*%s)*(1.+TMath::Erf((%s-%s)/%s))/2."%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp) )


            ##add a little shift
            #rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-0.2,0.);
            #rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,78.,10.,1400.);
            #rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,100.);
            #rrv_deltax = RooRealVar("rrv_deltax"+label+"_"+self.channel,"rrv_deltax"+label+"_"+self.channel,0,-10,10);
            #rrv_deltax.setConstant(1);
            #rrv_x_shift = RooFormulaVar("rrv_x_shift"+label+"_"+self.channel,"@0+@1",RooArgList(rrv_x, rrv_deltax));
            #model_pdf = ROOT.RooErfExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x_shift,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);


        if in_model_name == "ErfExp_v1" : #different init-value and range
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.006,-0.1,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,450.,400.,550.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,70.,10,100.);
            model_pdf = ROOT.RooErfExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            #model_pdf = RooGenericPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, "TMath::Exp(%s*%s)*(1.+TMath::Erf((%s-%s)/%s))/2."%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp) )

        if in_model_name == "ErfExp_v2" : #different init-value and range
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.005,-0.1,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,450.,400.,500.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel, 50.,10,100.);
            rrv_residue_ErfExp = RooRealVar("rrv_residue_ErfExp"+label+"_"+self.channel,"rrv_residue_ErfExp"+label+"_"+self.channel,0.,0.,1.);
            #model_pdf = ROOT.RooErfExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            model_pdf = RooGenericPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, "(TMath::Exp(%s*%s) + %s)*(1.+TMath::Erf((%s-%s)/%s))/2. "%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_residue_ErfExp.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp,rrv_residue_ErfExp) )

        if in_model_name == "ErfExp_v3" : #different init-value and range
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.005,-0.1,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,450.,400,500.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel, 50.,10,100.);
            rrv_residue_ErfExp = RooRealVar("rrv_residue_ErfExp"+label+"_"+self.channel,"rrv_residue_ErfExp"+label+"_"+self.channel,0.,0.,1.);
            rrv_high_ErfExp = RooRealVar("rrv_high_ErfExp"+label+"_"+self.channel,"rrv_high_ErfExp"+label+"_"+self.channel,1.,0.,400);
            rrv_high_ErfExp.setConstant(kTRUE);
            model_pdf = RooGenericPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, "(TMath::Exp(%s*%s) + %s)* TMath::Power( ((1+TMath::Erf((%s-%s)/%s))/2.), %s )"%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_residue_ErfExp.GetName(),rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName(), rrv_high_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_high_ErfExp,rrv_width_ErfExp,rrv_residue_ErfExp) )
      
            
        if in_model_name == "ErfExpGaus":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-0.4,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,100.,10.,300.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,100.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,82,78,87);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,7,4,10);
            rrv_high = RooRealVar("rrv_high"+label+"_"+self.channel,"rrv_high"+label+"_"+self.channel,0.7,0.,1.);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            #erfExp = RooGenericPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel, "TMath::Exp(%s*%s)*(1.+TMath::Erf((%s-%s)/%s))/2."%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp) )
            gaus = RooGaussian("gaus"+label+"_"+self.channel,"gaus"+label+"_"+self.channel, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus),RooArgList(rrv_high))

        if in_model_name == "ErfExpGaus_sp":#offset == mean
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-0.2,0.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,200.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,84,78,88);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,7,4,10);
            rrv_high = RooRealVar("rrv_high"+label+"_"+self.channel,"rrv_high"+label+"_"+self.channel,0.5,0.,1.);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_mean_gaus,rrv_width_ErfExp);
            gaus = RooGaussian("gaus"+label+"_"+self.channel,"gaus"+label+"_"+self.channel, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus),RooArgList(rrv_high))

        if in_model_name == "ErfExpGaus_v0":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-0.2,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,100.,10.,140.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,100.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,84,78,88);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,7,4,10);
            rrv_high = RooRealVar("rrv_high"+label+"_"+self.channel,"rrv_high"+label+"_"+self.channel,0.7,0.,1.);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            #erfExp = RooGenericPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel, "TMath::Exp(%s*%s)*(1.+TMath::Erf((%s-%s)/%s))/2."%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp) )
            gaus = RooGaussian("gaus"+label+"_"+self.channel,"gaus"+label+"_"+self.channel, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus),RooArgList(rrv_high))
    
        if in_model_name == "ErfExpGaus_v1":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.007,-0.1,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,800.,10.,1400.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,24.,10,150.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,700,500,1200);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,150,10,300);
            rrv_high = RooRealVar("rrv_high"+label+"_"+self.channel,"rrv_high"+label+"_"+self.channel,0.1,0.,1.);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            #erfExp = RooGenericPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel, "TMath::Exp(%s*%s)*(1.+TMath::Erf((%s-%s)/%s))/2."%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp) )
            gaus = RooGaussian("gaus"+label+"_"+self.channel,"gaus"+label+"_"+self.channel, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus),RooArgList(rrv_high))
        if in_model_name == "ErfExpGaus_sp_v1":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.007,-0.1,0.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,24.,10,150.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,900,860,1200);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,150,10,300);
            rrv_high = RooRealVar("rrv_high"+label+"_"+self.channel,"rrv_high"+label+"_"+self.channel,0.1,0.,1.);
            #erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_mean_gaus,rrv_width_ErfExp);
            gaus = RooGaussian("gaus"+label+"_"+self.channel,"gaus"+label+"_"+self.channel, rrv_x,rrv_mean_gaus,rrv_sigma_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus),RooArgList(rrv_high))
    
        if in_model_name == "ErfExpGaus_v2":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-10.,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,100.,10.,140.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,100.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,84,78,88);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,7,4,10);
            rrv_high = RooRealVar("rrv_high"+label+"_"+self.channel,"rrv_high"+label+"_"+self.channel,200.,0.,1000.);
            model_pdf = ROOT.RooErfExp_Gaus_Pdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp,rrv_mean_gaus,rrv_sigma_gaus,rrv_high );
    
        if in_model_name == "ErfExp2Gaus":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.05,-0.2,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,100.,10.,140.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,100.);
            rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,84,78,88);
            rrv_mean2_gaus=RooRealVar("rrv_mean2_gaus"+label+"_"+self.channel,"rrv_mean2_gaus"+label+"_"+self.channel,180,170,190);
            rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,7,4,10);
            rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,10,7,15);
            rrv_high1 = RooRealVar("rrv_high1"+label+"_"+self.channel,"rrv_high1"+label+"_"+self.channel,0.6,0.,1.);
            rrv_high2 = RooRealVar("rrv_high2"+label+"_"+self.channel,"rrv_high2"+label+"_"+self.channel,0.4,0.,1.);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            #erfExp = RooGenericPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel, "TMath::Exp(%s*%s)*(1.+TMath::Erf((%s-%s)/%s))/2."%(rrv_c_ErfExp.GetName(),rrv_x.GetName(), rrv_x.GetName(),rrv_offset_ErfExp.GetName(), rrv_width_ErfExp.GetName()), RooArgList(rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp) )
            gaus1 = RooGaussian("gaus1"+label+"_"+self.channel,"gaus1"+label+"_"+self.channel, rrv_x,rrv_mean1_gaus,rrv_sigma1_gaus);
            gaus2 = RooGaussian("gaus2"+label+"_"+self.channel,"gaus2"+label+"_"+self.channel, rrv_x,rrv_mean2_gaus,rrv_sigma2_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus1,gaus2),RooArgList(rrv_high1,rrv_high2))

        if in_model_name == "2Gaus_ttbar":
            mean1_tmp     =8.3145e+01;  mean1_tmp_err     =1.63e-01;
            deltamean_tmp =6.6321e+00;  deltamean_tmp_err =1.21e+00;
            sigma1_tmp    =7.5097e+00;  sigma1_tmp_err    =2.01e-01;
            scalesigma_tmp=3.8707e+00;  scalesigma_tmp_err=2.20e-01;
            frac_tmp      =6.4728e-01;  frac_tmp_err      =2.03e-02; 

            if self.wtagger_cut==0.43:
                mean1_tmp     =8.3089e+01;  mean1_tmp_err     =1.61e-01;
                deltamean_tmp =9.3065e+00;  deltamean_tmp_err =1.67e+00;
                sigma1_tmp    =7.5280e+00;  sigma1_tmp_err    =1.91e-01;
                scalesigma_tmp=3.4619e+00;  scalesigma_tmp_err=2.29e-01;
                frac_tmp      =7.4246e-01;  frac_tmp_err      =2.11e-02; 

            if self.channel=="el":
                if self.workspace4fit_.var("rrv_mean1_gaus%s_mu"%(label)) and self.workspace4fit_.var("rrv_sigma1_gaus%s_mu"%(label)):
                    rrv_mean1_gaus=self.workspace4fit_.var("rrv_mean1_gaus%s_mu"%(label));
                    rrv_sigma1_gaus=self.workspace4fit_.var("rrv_sigma1_gaus%s_mu"%(label));
                else:
                    rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-4, mean1_tmp+4);
                    rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-4,sigma1_tmp+4 );
            if self.channel=="mu":
                if self.workspace4fit_.var("rrv_mean1_gaus%s_el"%(label)) and self.workspace4fit_.var("rrv_sigma1_gaus%s_el"%(label)):
                    rrv_mean1_gaus=self.workspace4fit_.var("rrv_mean1_gaus%s_el"%(label));
                    rrv_sigma1_gaus=self.workspace4fit_.var("rrv_sigma1_gaus%s_el"%(label));
                else:
                    rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-4, mean1_tmp+4);
                    rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-4,sigma1_tmp+4 );



            #rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-4, mean1_tmp+4);
            #rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-4,sigma1_tmp+4 );
            gaus1 = RooGaussian("gaus1"+label+"_"+self.channel,"gaus1"+label+"_"+self.channel, rrv_x,rrv_mean1_gaus,rrv_sigma1_gaus);

            rrv_deltamean_gaus=RooRealVar("rrv_deltamean_gaus"+label+"_"+self.channel,"rrv_deltamean_gaus"+label+"_"+self.channel,deltamean_tmp);#, deltamean_tmp-deltamean_tmp_err*4, deltamean_tmp+deltamean_tmp_err*4); 
            rrv_mean2_gaus =RooFormulaVar("rrv_mean2_gaus"+label+"_"+self.channel,"@0+@1",RooArgList(rrv_mean1_gaus, rrv_deltamean_gaus));
            rrv_scalesigma_gaus=RooRealVar("rrv_scalesigma_gaus"+label+"_"+self.channel,"rrv_scalesigma_gaus"+label+"_"+self.channel,scalesigma_tmp);#, scalesigma_tmp-scalesigma_tmp_err*4, scalesigma_tmp+scalesigma_tmp_err*4); 
            rrv_sigma2_gaus=RooFormulaVar("rrv_sigma2_gaus"+label+"_"+self.channel,"@0*@1", RooArgList(rrv_sigma1_gaus,rrv_scalesigma_gaus));
            gaus2 = RooGaussian("gaus2"+label+"_"+self.channel,"gaus2"+label+"_"+self.channel, rrv_x,rrv_mean2_gaus,rrv_sigma2_gaus);
            rrv_frac = RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,frac_tmp)#, frac_tmp-frac_tmp_err*4, frac_tmp+frac_tmp_err*4);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(gaus1,gaus2),RooArgList(rrv_frac),1)

        if in_model_name == "GausChebychev_ttbar_failtau2tau1cut":
            p0_tmp  =-4.9980e-01;  p0_tmp_err  =5.66e-02;
            p1_tmp  =-7.4171e-02;  p1_tmp_err  =7.31e-02;
            frac_tmp= 2.0655e-01;  frac_tmp_err=2.90e-02; 

            if self.wtagger_cut==0.43:
                p0_tmp  =-2.3067e-01;  p0_tmp_err  =4.12e-02;
                p1_tmp  =-2.6924e-01;  p1_tmp_err  =5.69e-02;
                frac_tmp= 3.2004e-01;  frac_tmp_err=2.04e-02; 

            if TString(label).Contains("data"):
                gaus = self.workspace4fit_.pdf("gaus1_ttbar_data_"+self.channel);
            elif TString(label).Contains("TotalMC"):
                gaus = self.workspace4fit_.pdf("gaus1_ttbar_TotalMC_"+self.channel);

            rrv_p0_cheb=RooRealVar("rrv_p0_cheb"+label+"_"+self.channel,"rrv_p0_cheb"+label+"_"+self.channel,p0_tmp)#,p0_tmp-p0_tmp_err*4,p0_tmp+p0_tmp_err*4);
            rrv_p1_cheb=RooRealVar("rrv_p1_cheb"+label+"_"+self.channel,"rrv_p1_cheb"+label+"_"+self.channel,p1_tmp)#,p1_tmp-p1_tmp_err*4,p1_tmp+p1_tmp_err*4);
            cheb = RooChebychev("cheb"+label+"_"+self.channel,"cheb"+label+"_"+self.channel, rrv_x, RooArgList(rrv_p0_cheb, rrv_p1_cheb) );

            rrv_frac = RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,frac_tmp);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(gaus,cheb),RooArgList(rrv_frac),1)
            #self.addConstraint(rrv_p0_cheb,p0_tmp, p0_tmp_err,ConstraintsList);
            #self.addConstraint(rrv_p1_cheb,p1_tmp, p1_tmp_err,ConstraintsList);

        if in_model_name == "2Gaus_ttbar_failtau2tau1cut":
            mean1_tmp     =8.3209e+01;  mean1_tmp_err     =1.17e-01;
            deltamean_tmp =1.1427e+00;  deltamean_tmp_err =1.03e+00;
            sigma1_tmp    =7.4932e+00;  sigma1_tmp_err    =1.44e-01;
            scalesigma_tmp=4.5922e+00;  scalesigma_tmp_err=2.87e-01;
            frac_tmp      =5.7910e-01;  frac_tmp_err      =1.59e-02; 

            #rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-mean1_tmp_err*4, mean1_tmp+mean1_tmp_err*4);
            rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-4, mean1_tmp+4);
            #rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-sigma1_tmp_err*4,sigma1_tmp+sigma1_tmp_err*4 );
            rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-4,sigma1_tmp+4 );
            gaus1 = RooGaussian("gaus1"+label+"_"+self.channel,"gaus1"+label+"_"+self.channel, rrv_x,rrv_mean1_gaus,rrv_sigma1_gaus);
            rrv_deltamean_gaus=RooRealVar("rrv_deltamean_gaus"+label+"_"+self.channel,"rrv_deltamean_gaus"+label+"_"+self.channel,deltamean_tmp);#, deltamean_tmp-deltamean_tmp_err*4, deltamean_tmp+deltamean_tmp_err*4); 
            rrv_mean2_gaus =RooFormulaVar("rrv_mean2_gaus"+label+"_"+self.channel,"@0+@1",RooArgList(rrv_mean1_gaus, rrv_deltamean_gaus));
            rrv_scalesigma_gaus=RooRealVar("rrv_scalesigma_gaus"+label+"_"+self.channel,"rrv_scalesigma_gaus"+label+"_"+self.channel,scalesigma_tmp);#, scalesigma_tmp-scalesigma_tmp_err*4, scalesigma_tmp+scalesigma_tmp_err*4); 
            rrv_sigma2_gaus=RooFormulaVar("rrv_sigma2_gaus"+label+"_"+self.channel,"@0*@1", RooArgList(rrv_sigma1_gaus,rrv_scalesigma_gaus));
            gaus2 = RooGaussian("gaus2"+label+"_"+self.channel,"gaus2"+label+"_"+self.channel, rrv_x,rrv_mean2_gaus,rrv_sigma2_gaus);
            rrv_frac = RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,frac_tmp);#, frac_tmp-frac_tmp_err*4, frac_tmp+frac_tmp_err*4);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(gaus1,gaus2),RooArgList(rrv_frac),1)
            #self.addConstraint(rrv_sigma1_gaus,sigma1_tmp, sigma1_tmp_err,ConstraintsList);


        if in_model_name == "2Gaus_ttbar_failtau2tau1cut":
            mean1_tmp     =8.3209e+01;  mean1_tmp_err     =1.17e-01;
            deltamean_tmp =1.1427e+00;  deltamean_tmp_err =1.03e+00;
            sigma1_tmp    =7.4932e+00;  sigma1_tmp_err    =1.44e-01;
            scalesigma_tmp=4.5922e+00;  scalesigma_tmp_err=2.87e-01;
            frac_tmp      =5.7910e-01;  frac_tmp_err      =1.59e-02; 

            #rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-mean1_tmp_err*4, mean1_tmp+mean1_tmp_err*4);
            rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,mean1_tmp, mean1_tmp-4, mean1_tmp+4);
            #rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-sigma1_tmp_err*4,sigma1_tmp+sigma1_tmp_err*4 );
            rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,sigma1_tmp, sigma1_tmp-4,sigma1_tmp+4 );
            gaus1 = RooGaussian("gaus1"+label+"_"+self.channel,"gaus1"+label+"_"+self.channel, rrv_x,rrv_mean1_gaus,rrv_sigma1_gaus);
            rrv_deltamean_gaus=RooRealVar("rrv_deltamean_gaus"+label+"_"+self.channel,"rrv_deltamean_gaus"+label+"_"+self.channel,deltamean_tmp);#, deltamean_tmp-deltamean_tmp_err*4, deltamean_tmp+deltamean_tmp_err*4); 
            rrv_mean2_gaus =RooFormulaVar("rrv_mean2_gaus"+label+"_"+self.channel,"@0+@1",RooArgList(rrv_mean1_gaus, rrv_deltamean_gaus));
            rrv_scalesigma_gaus=RooRealVar("rrv_scalesigma_gaus"+label+"_"+self.channel,"rrv_scalesigma_gaus"+label+"_"+self.channel,scalesigma_tmp);#, scalesigma_tmp-scalesigma_tmp_err*4, scalesigma_tmp+scalesigma_tmp_err*4); 
            rrv_sigma2_gaus=RooFormulaVar("rrv_sigma2_gaus"+label+"_"+self.channel,"@0*@1", RooArgList(rrv_sigma1_gaus,rrv_scalesigma_gaus));
            gaus2 = RooGaussian("gaus2"+label+"_"+self.channel,"gaus2"+label+"_"+self.channel, rrv_x,rrv_mean2_gaus,rrv_sigma2_gaus);
            rrv_frac = RooRealVar("rrv_frac"+label+"_"+self.channel,"rrv_frac"+label+"_"+self.channel,frac_tmp);#, frac_tmp-frac_tmp_err*4, frac_tmp+frac_tmp_err*4);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(gaus1,gaus2),RooArgList(rrv_frac),1)
            #self.addConstraint(rrv_sigma1_gaus,sigma1_tmp, sigma1_tmp_err,ConstraintsList);

        if in_model_name == "ErfExp_ttbar":
            c0_tmp    =   -2.8628e-02 ; c0_tmp_err     = 6.08e-03;
            offset_tmp=    7.6259e+01 ; offset_tmp_err = 9.17e+00;
            width_tmp =    3.4207e+01 ; width_tmp_err  = 3.18e+00; 
            if self.wtagger_cut==0.43:
                c0_tmp    =   -3.0807e-02 ; c0_tmp_err     = 8.16e-03;
                offset_tmp=    8.2863e+01 ; offset_tmp_err = 9.66e+00;
                width_tmp =    3.1119e+01 ; width_tmp_err  = 2.80e+00; 

            #rrv_c_ErfExp     = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,c0_tmp, c0_tmp-c0_tmp_err*4, c0_tmp+c0_tmp_err*4  );
            rrv_c_ErfExp     = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,c0_tmp, c0_tmp-4e-2, c0_tmp+4e-2  );
            rrv_offset_ErfExp= RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel, offset_tmp, offset_tmp-offset_tmp_err*4,offset_tmp+offset_tmp_err*4);
            #rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel, width_tmp, width_tmp-width_tmp_err*4, width_tmp+width_tmp_err*4);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel, width_tmp, width_tmp-10, width_tmp+10);
            model_pdf = ROOT.RooErfExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);

            self.addConstraint(rrv_c_ErfExp,c0_tmp, c0_tmp_err,ConstraintsList);
            self.addConstraint(rrv_offset_ErfExp,offset_tmp, offset_tmp_err,ConstraintsList);
            self.addConstraint(rrv_width_ErfExp,width_tmp, width_tmp_err,ConstraintsList);

        if in_model_name == "ErfExp_ttbar_failtau2tau1cut":
            c0_tmp    =   -1.1140e-01 ; c0_tmp_err     = 1.22e-02; 
            offset_tmp=    3.2034e+02 ; offset_tmp_err = 2.33e+01;
            width_tmp =    7.5768e+01 ; width_tmp_err  = 2.97e+00;
            if self.wtagger_cut==0.43:
               c0_tmp    =   -5.0476e-02 ; c0_tmp_err     = 6.92e-03; 
               offset_tmp=    1.1323e+02 ; offset_tmp_err = 1.94e+01;
               width_tmp =    5.8616e+01 ; width_tmp_err  = 4.00e+00;

            rrv_c_ErfExp     = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,c0_tmp, c0_tmp-4e-2, c0_tmp+4e-2 );
            rrv_offset_ErfExp= RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel, offset_tmp);#, offset_tmp-offset_tmp_err*4,offset_tmp+offset_tmp_err*4);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel, width_tmp);#, width_tmp-10, width_tmp+10);
            model_pdf = ROOT.RooErfExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);

            self.addConstraint(rrv_c_ErfExp,c0_tmp, c0_tmp_err,ConstraintsList);
            #self.addConstraint(rrv_offset_ErfExp,offset_tmp, offset_tmp_err,ConstraintsList);
            #self.addConstraint(rrv_width_ErfExp,width_tmp, width_tmp_err,ConstraintsList);


        #if in_model_name == "ErfExp_ttbar_failtau2tau1cut":
        #    c0_tmp    =   -2.3262e-02  ; c0_tmp_err     =  7.87e-04;
        #    rrv_c_Exp     = RooRealVar("rrv_c_Exp"+label+"_"+self.channel,"rrv_c_Exp"+label+"_"+self.channel,c0_tmp, c0_tmp-4e-2, c0_tmp+4e-2 );
        #    model_pdf = ROOT.RooExponential("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c_Exp);
        #    self.addConstraint(rrv_c_Exp,c0_tmp, c0_tmp_err,ConstraintsList);

        if in_model_name == "ErfExp2Gaus_ttbar":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel, -9.72533e-02, -9.72533e-02-2*6.05691e-03, -9.72533e-02+2*6.05691e-03 );
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,2.21236e+02, 2.21236e+02-2*9.53939e+00, 2.21236e+02+2*9.53939e+00 );
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,5.79251e+01,5.79251e+01-2*1.22221e+00,5.79251e+01+2*1.22221e+00);
            rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,8.36227e+01,8.36227e+01-2* 1.60148e-01,8.36227e+01+2* 1.60148e-01);
            rrv_mean2_gaus=RooRealVar("rrv_mean2_gaus"+label+"_"+self.channel,"rrv_mean2_gaus"+label+"_"+self.channel,8.45644e+01 ,8.45644e+01-2* 9.21003e-01 ,8.45644e+01+2* 9.21003e-01 );
            rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,7.45239e+00,7.45239e+00-2*2.05052e-01,7.45239e+00+2*2.05052e-01);
            rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,3.39773e+01,3.39773e+01-2*2.44179e+00,3.39773e+01+2*2.44179e+00);
            rrv_high1 = RooRealVar("rrv_high1"+label+"_"+self.channel,"rrv_high1"+label+"_"+self.channel,0.5,0.,1.);
            rrv_high2 = RooRealVar("rrv_high2"+label+"_"+self.channel,"rrv_high2"+label+"_"+self.channel,0.5622,0.51,0.61);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            gaus1 = RooGaussian("gaus1"+label+"_"+self.channel,"gaus1"+label+"_"+self.channel, rrv_x,rrv_mean1_gaus,rrv_sigma1_gaus);
            gaus2 = RooGaussian("gaus2"+label+"_"+self.channel,"gaus2"+label+"_"+self.channel, rrv_x,rrv_mean2_gaus,rrv_sigma2_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus1,gaus2),RooArgList(rrv_high1,rrv_high2),1)
        if in_model_name == "ErfExp2Gaus_ttbar_failtau2tau1cut":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-2.81053e-02 ,-2.81053e-02-2*5.82712e-03 ,-2.81053e-02+2*5.82712e-03 );
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,7.63158e+01,7.63158e+01-2*8.66322e+00,7.63158e+01+2*8.66322e+00);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,3.38156e+01,3.38156e+01-2*3.02392e+00,3.38156e+01+2*3.02392e+00);
            rrv_mean1_gaus=RooRealVar("rrv_mean1_gaus"+label+"_"+self.channel,"rrv_mean1_gaus"+label+"_"+self.channel,8.34758e+01,8.34758e+01-2*1.62468e-01,8.34758e+01+2*1.62468e-01);
            rrv_mean2_gaus=RooRealVar("rrv_mean2_gaus"+label+"_"+self.channel,"rrv_mean2_gaus"+label+"_"+self.channel,8.99116e+01,8.99116e+01-2*7.47952e-01,8.99116e+01+2*7.47952e-01);
            rrv_sigma1_gaus=RooRealVar("rrv_sigma1_gaus"+label+"_"+self.channel,"rrv_sigma1_gaus"+label+"_"+self.channel,7.45827e+00,7.45827e+00-2*1.95598e-01,7.45827e+00+2*1.95598e-01);
            rrv_sigma2_gaus=RooRealVar("rrv_sigma2_gaus"+label+"_"+self.channel,"rrv_sigma2_gaus"+label+"_"+self.channel,2.90745e+01,2.90745e+01-2*1.77035e+00,2.90745e+01+2*1.77035e+00);
            rrv_high1 = RooRealVar("rrv_high1"+label+"_"+self.channel,"rrv_high1"+label+"_"+self.channel,0.5,0.,1.);
            rrv_high2 = RooRealVar("rrv_high2"+label+"_"+self.channel,"rrv_high2"+label+"_"+self.channel,0.6323,0.57,0.7);
            erfExp = ROOT.RooErfExpPdf("erfExp"+label+"_"+self.channel,"erfExp"+label+"_"+self.channel,rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp);
            gaus1 = RooGaussian("gaus1"+label+"_"+self.channel,"gaus1"+label+"_"+self.channel, rrv_x,rrv_mean1_gaus,rrv_sigma1_gaus);
            gaus2 = RooGaussian("gaus2"+label+"_"+self.channel,"gaus2"+label+"_"+self.channel, rrv_x,rrv_mean2_gaus,rrv_sigma2_gaus);
            model_pdf =RooAddPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,RooArgList(erfExp,gaus1,gaus2),RooArgList(rrv_high1,rrv_high2),1)
    
        if in_model_name == "ErfExpVoigGaus":
            rrv_c_ErfExp = RooRealVar("rrv_c_ErfExp"+label+"_"+self.channel,"rrv_c_ErfExp"+label+"_"+self.channel,-0.1,-10.,0.);
            rrv_offset_ErfExp = RooRealVar("rrv_offset_ErfExp"+label+"_"+self.channel,"rrv_offset_ErfExp"+label+"_"+self.channel,100.,10.,140.);
            rrv_width_ErfExp = RooRealVar("rrv_width_ErfExp"+label+"_"+self.channel,"rrv_width_ErfExp"+label+"_"+self.channel,30.,10,100.);
            rrv_mean_voig=RooRealVar("rrv_mean_voig"+label+"_"+self.channel,"rrv_mean_voig"+label+"_"+self.channel,84,78,88);
            rrv_width_voig=RooRealVar("rrv_width_voig"+label+"_"+self.channel,"rrv_width_voig"+label+"_"+self.channel,7,1,20);
            rrv_sigma_voig=RooRealVar("rrv_sigma_voig"+label+"_"+self.channel,"rrv_sigma_voig"+label+"_"+self.channel,5,1,100);
            rrv_high1 = RooRealVar("rrv_high1"+label+"_"+self.channel,"rrv_high1"+label+"_"+self.channel,1,0.,200.);
            rrv_mean_gaus=RooRealVar("rrv_mean_gaus"+label+"_"+self.channel,"rrv_mean_gaus"+label+"_"+self.channel,174)#,160,187);
            rrv_sigma_gaus=RooRealVar("rrv_sigma_gaus"+label+"_"+self.channel,"rrv_sigma_gaus"+label+"_"+self.channel,20)#,0.1,100);
            rrv_high2 = RooRealVar("rrv_high2"+label+"_"+self.channel,"rrv_high2"+label+"_"+self.channel,0.)#,0.,0.);
            model_pdf = ROOT.RooErfExp_Voig_Gaus_Pdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rrv_c_ErfExp,rrv_offset_ErfExp,rrv_width_ErfExp,rrv_mean_voig,rrv_width_voig,rrv_sigma_voig,rrv_high1,rrv_mean_gaus,rrv_sigma_gaus,rrv_high2 );

        if in_model_name == "User1":
            rrv_p0=RooRealVar("rrv_p0_User1"+label+"_"+self.channel,"rrv_p0_User1"+label+"_"+self.channel, 30,  10, 90);
            rrv_p1=RooRealVar("rrv_p1_User1"+label+"_"+self.channel,"rrv_p1_User1"+label+"_"+self.channel, -4,  -9, -2);
            #rrv_p2=RooRealVar("rrv_p2_User1"+label+"_"+self.channel,"rrv_p2_User1"+label+"_"+self.channel, 0)#,-100,100)#,200,1000)#,50,1000)#,-200,200);
            model_pdf=RooUser1Pdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_p0,rrv_p1);

        if in_model_name == "QCD":
            rrv_p0=RooRealVar("rrv_p0_QCD"+label+"_"+self.channel,"rrv_p0_QCD"+label+"_"+self.channel,  0,-200,200);
            rrv_p1=RooRealVar("rrv_p1_QCD"+label+"_"+self.channel,"rrv_p1_QCD"+label+"_"+self.channel,  0,-200,200);
            rrv_p2=RooRealVar("rrv_p2_QCD"+label+"_"+self.channel,"rrv_p2_QCD"+label+"_"+self.channel,  0,-200,200);
            model_pdf=RooQCDPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_p0,rrv_p1,rrv_p2);

        if in_model_name == "QCD_v2":#can replace exp 
            rrv_p0=RooRealVar("rrv_p0_QCD"+label+"_"+self.channel,"rrv_p0_QCD"+label+"_"+self.channel, -15,-50,0);
            rrv_p1=RooRealVar("rrv_p1_QCD"+label+"_"+self.channel,"rrv_p1_QCD"+label+"_"+self.channel,  20,0,250);
            rrv_p2=RooRealVar("rrv_p2_QCD"+label+"_"+self.channel,"rrv_p2_QCD"+label+"_"+self.channel,0,-20,20);
            model_pdf=RooQCDPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_p0,rrv_p1,rrv_p2);

        if in_model_name == "Pow" or in_model_name == "Pow_sr" :#can replace exp
            rrv_c=RooRealVar("rrv_c_Pow"+label+"_"+self.channel,"rrv_c_Pow"+label+"_"+self.channel, -5, -20, 0);
            model_pdf=RooPowPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x, rrv_c );
 
        if in_model_name == "Pow2":
            rrv_c0=RooRealVar("rrv_c0_Pow2"+label+"_"+self.channel,"rrv_c0_Pow2"+label+"_"+self.channel, 5, 0, 20);
            rrv_c1=RooRealVar("rrv_c1_Pow2"+label+"_"+self.channel,"rrv_c1_Pow2"+label+"_"+self.channel, 0, -5 , 5);
            model_pdf=RooPow2Pdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x, rrv_c0, rrv_c1 );

        if in_model_name == "ErfPow_v1":#can replace erf*exp 
            rrv_c=RooRealVar("rrv_c_ErfPow"+label+"_"+self.channel,"rrv_c_ErfPow"+label+"_"+self.channel, -5,-10,0);
            rrv_offset=RooRealVar("rrv_offset_ErfPow"+label+"_"+self.channel,"rrv_offset_ErfPow"+label+"_"+self.channel, 450,350,550);
            rrv_width=RooRealVar("rrv_width_ErfPow"+label+"_"+self.channel,"rrv_width_ErfPow"+label+"_"+self.channel,50,20,90);
            model_pdf=RooErfPowPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c,rrv_offset,rrv_width);

        if in_model_name == "ErfPow2_v1":#can replace erf*exp 
            rrv_c0=RooRealVar("rrv_c0_ErfPow2"+label+"_"+self.channel,"rrv_c0_ErfPow2"+label+"_"+self.channel,14,1,30);
            rrv_c1=RooRealVar("rrv_c1_ErfPow2"+label+"_"+self.channel,"rrv_c1_ErfPow2"+label+"_"+self.channel, 5,-5,10);
            rrv_offset=RooRealVar("rrv_offset_ErfPow2"+label+"_"+self.channel,"rrv_offset_ErfPow2"+label+"_"+self.channel, 450,400,520);
            rrv_width=RooRealVar("rrv_width_ErfPow2"+label+"_"+self.channel,"rrv_width_ErfPow2"+label+"_"+self.channel,30,10,80);
            model_pdf=RooErfPow2Pdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c0,rrv_c1,rrv_offset,rrv_width);

        if in_model_name == "ErfPow2_v1_sr":#can replace erf*exp 
            rrv_c0=RooRealVar("rrv_c0_ErfPow2"+label+"_"+self.channel,"rrv_c0_ErfPow2"+label+"_"+self.channel, 4,2, 8);
            rrv_c1=RooRealVar("rrv_c1_ErfPow2"+label+"_"+self.channel,"rrv_c1_ErfPow2"+label+"_"+self.channel, -0.5,-2,0);
            rrv_offset=RooRealVar("rrv_offset_ErfPow2"+label+"_"+self.channel,"rrv_offset_ErfPow2"+label+"_"+self.channel, 490,440,520);
            rrv_width=RooRealVar("rrv_width_ErfPow2"+label+"_"+self.channel,"rrv_width_ErfPow2"+label+"_"+self.channel,50,30,80);
            model_pdf=RooErfPow2Pdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c0,rrv_c1,rrv_offset,rrv_width);


        if in_model_name == "ErfPowExp_v1":#can replace erf*exp 
            #rrv_c0=RooRealVar("rrv_c0_ErfPowExp"+label+"_"+self.channel,"rrv_c0_ErfPowExp"+label+"_"+self.channel,13,5,30);
            #rrv_c1=RooRealVar("rrv_c1_ErfPowExp"+label+"_"+self.channel,"rrv_c1_ErfPowExp"+label+"_"+self.channel, 0,-2,2);
            rrv_c0=RooRealVar("rrv_c0_ErfPowExp"+label+"_"+self.channel,"rrv_c0_ErfPowExp"+label+"_"+self.channel,13,5,40);
            rrv_c1=RooRealVar("rrv_c1_ErfPowExp"+label+"_"+self.channel,"rrv_c1_ErfPowExp"+label+"_"+self.channel, 2,0,4);
            rrv_offset=RooRealVar("rrv_offset_ErfPowExp"+label+"_"+self.channel,"rrv_offset_ErfPowExp"+label+"_"+self.channel, 450,420,520);
            rrv_width=RooRealVar("rrv_width_ErfPowExp"+label+"_"+self.channel,"rrv_width_ErfPowExp"+label+"_"+self.channel,30,10,80);
            model_pdf=RooErfPowExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c0,rrv_c1,rrv_offset,rrv_width);

        if in_model_name == "ErfPowExp_v1_sr":#can replace erf*exp 
            rrv_c0=RooRealVar("rrv_c0_ErfPowExp"+label+"_"+self.channel,"rrv_c0_ErfPowExp"+label+"_"+self.channel,6,2,15);
            rrv_c1=RooRealVar("rrv_c1_ErfPowExp"+label+"_"+self.channel,"rrv_c1_ErfPowExp"+label+"_"+self.channel, -1,-3,2);
            rrv_offset=RooRealVar("rrv_offset_ErfPowExp"+label+"_"+self.channel,"rrv_offset_ErfPowExp"+label+"_"+self.channel, 490,440,520);
            rrv_width=RooRealVar("rrv_width_ErfPowExp"+label+"_"+self.channel,"rrv_width_ErfPowExp"+label+"_"+self.channel,50,30,70);
            model_pdf=RooErfPowExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c0,rrv_c1,rrv_offset,rrv_width);

        if in_model_name == "ErfPowExp_v1_0":#difference inital value
            rrv_c0=RooRealVar("rrv_c0_ErfPowExp"+label+"_"+self.channel,"rrv_c0_ErfPowExp"+label+"_"+self.channel,20,15,40);
            rrv_c1=RooRealVar("rrv_c1_ErfPowExp"+label+"_"+self.channel,"rrv_c1_ErfPowExp"+label+"_"+self.channel, 1.6,0.5,5);
            rrv_offset=RooRealVar("rrv_offset_ErfPowExp"+label+"_"+self.channel,"rrv_offset_ErfPowExp"+label+"_"+self.channel, 470,420,520);
            rrv_width=RooRealVar("rrv_width_ErfPowExp"+label+"_"+self.channel,"rrv_width_ErfPowExp"+label+"_"+self.channel,47,30,60);
            model_pdf=RooErfPowExpPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum,rrv_x,rrv_c0,rrv_c1,rrv_offset,rrv_width);

        if in_model_name == "Keys":
            rdataset=self.workspace4fit_.data("rdataset_%s_signal_region_mlvj"%(self.higgs_sample))
            model_pdf = RooKeysPdf("model_pdf"+label+"_"+self.channel+mass_spectrum,"model_pdf"+label+"_"+self.channel+mass_spectrum, rrv_x,rdataset);

        getattr(self.workspace4fit_,"import")(model_pdf)
        return self.workspace4fit_.pdf("model_pdf"+label+"_"+self.channel+mass_spectrum)

    ##################### ---------------------------------------------------
    def addConstraint(self, rrv_x, x_mean, x_sigma, ConstraintsList):
            rrv_x_mean = RooRealVar(rrv_x.GetName()+"_mean",rrv_x.GetName()+"_mean",x_mean );
            rrv_x_sigma = RooRealVar(rrv_x.GetName()+"_sigma",rrv_x.GetName()+"_sigma",x_sigma );
            constrainpdf_x=RooGaussian("constrainpdf_"+rrv_x.GetName(),"constrainpdf_"+rrv_x.GetName(),rrv_x, rrv_x_mean, rrv_x_sigma);
            getattr(self.workspace4fit_,"import")(constrainpdf_x)
            ConstraintsList.append(constrainpdf_x.GetName()); 

    ##################### ---------------------------------------------------
    def make_Model(self, label, in_model_name, mass_spectrum="_mj", ConstraintsList=[]):
        rrv_number = RooRealVar("rrv_number"+label+"_"+self.channel+mass_spectrum,"rrv_number"+label+"_"+self.channel+mass_spectrum,500,0.,1e7);
        model_pdf  = self.make_Pdf(label,in_model_name,mass_spectrum,ConstraintsList)
        model_pdf.Print();
        model = RooExtendPdf("model"+label+"_"+self.channel+mass_spectrum,"model"+label+"_"+self.channel+mass_spectrum, model_pdf, rrv_number );
        getattr(self.workspace4fit_,"import")(rrv_number)
        getattr(self.workspace4fit_,"import")(model)
        model.Print();
        print "model"+label+"_"+self.channel+mass_spectrum 
        self.workspace4fit_.pdf("model"+label+"_"+self.channel+mass_spectrum).Print();
        return self.workspace4fit_.pdf("model"+label+"_"+self.channel+mass_spectrum);
    ##################### ---------------------------------------------------
    def make_Model_for_ttbar_controlsample(self, label, in_model_name, mass_spectrum="_mj", ConstraintsList=[]):
        if label=="_ttbar_data":
            rrv_number_total =RooRealVar("rrv_number_total_ttbar_data_"+self.channel,"rrv_number_total_ttbar_data_"+self.channel,500,0.,1e7); 
            eff_ttbar=RooRealVar("eff_ttbar_data_"+self.channel,"eff_ttbar_data_"+self.channel,0.8,0.4,1.0);
            rrv_number = RooFormulaVar("rrv_number"+label+"_"+self.channel+mass_spectrum, "@0*@1", RooArgList(rrv_number_total,eff_ttbar ) );
        elif label=="_ttbar_data_failtau2tau1cut":
            rrv_number_total =self.workspace4fit_.var("rrv_number_total_ttbar_data_"+self.channel);
            eff_ttbar=self.workspace4fit_.var("eff_ttbar_data_"+self.channel);
            rrv_number = RooFormulaVar("rrv_number"+label+"_"+self.channel+mass_spectrum, "(1-@0)*@1", RooArgList(eff_ttbar,rrv_number_total ) );
        elif label=="_ttbar_TotalMC":
            rrv_number_total =RooRealVar("rrv_number_total_ttbar_TotalMC_"+self.channel,"rrv_number_total_ttbar_TotalMC_"+self.channel,500,0.,1e7); 
            eff_ttbar=RooRealVar("eff_ttbar_TotalMC_"+self.channel,"eff_ttbar_TotalMC_"+self.channel,0.8,0.4,1.0);
            rrv_number = RooFormulaVar("rrv_number"+label+"_"+self.channel+mass_spectrum, "@0*@1", RooArgList(eff_ttbar,rrv_number_total ) );
        elif label=="_ttbar_TotalMC_failtau2tau1cut":
            rrv_number_total =self.workspace4fit_.var("rrv_number_total_ttbar_TotalMC_"+self.channel);
            eff_ttbar=self.workspace4fit_.var("eff_ttbar_TotalMC_"+self.channel);
            rrv_number = RooFormulaVar("rrv_number"+label+"_"+self.channel+mass_spectrum, "(1-@0)*@1", RooArgList(eff_ttbar,rrv_number_total ) );
        model_pdf  = self.make_Pdf(label,in_model_name,mass_spectrum,ConstraintsList)
        model_pdf.Print();
        model = RooExtendPdf("model"+label+"_"+self.channel+mass_spectrum,"model"+label+"_"+self.channel+mass_spectrum, model_pdf, rrv_number );
        #getattr(self.workspace4fit_,"import")(rrv_number)
        getattr(self.workspace4fit_,"import")(model)
        model.Print();
        print "model"+label+"_"+self.channel+mass_spectrum 
        self.workspace4fit_.pdf("model"+label+"_"+self.channel+mass_spectrum).Print();
        return self.workspace4fit_.pdf("model"+label+"_"+self.channel+mass_spectrum);    
    ##################### ---------------------------------------------------
    def get_mj_Model(self,label):
        return self.workspace4fit_.pdf("model"+label+"_"+self.channel+"_mj")

    ##################### ---------------------------------------------------
    def get_General_mj_Model(self, label ):
        rdataset_General_mj=self.workspace4fit_.data("rdataset%s_%s_mj"%(label,self.channel))
        model_General=self.get_mj_Model(label);
        #rdataset_General_mj.Print()
        #model_General.Print()
        parameters_General=model_General.getParameters(rdataset_General_mj);
        par=parameters_General.createIterator();
        par.Reset();
        param=par.Next()
        while (param):
            param.setConstant(kTRUE);
            #if TString(param.GetName()).Contains("rrv_number_"):
            #    if label=="_TTbar": xs_uncertainty=self.XS_TTbar_uncertainty;
            #    if label=="_VV":    xs_uncertainty=self.XS_STop_uncertainty;
            #    if label=="_STop":  xs_uncertainty=self.XS_VV_uncertainty;
            #    num_uncertainty=TMath.Sqrt(param.getError()*param.getError()+ param.getVal()*param.getVal()*xs_uncertainty*xs_uncertainty  );
            #    param.setRange(param.getVal()-10*num_uncertainty, param.getVal()+10*num_uncertainty);
            #    param.Print();
            #    param_mean= RooRealVar("%s_mean"%(param.GetName()),"%s_mean"%(param.GetName()),param.getVal())
            #    param_sigma=RooRealVar("%s_sigma"%(param.GetName()),"%s_sigma"%(param.GetName()),num_uncertainty)
            #    constrainpdf=RooGaussian("constrainpdf"+label+"_"+self.channel,"constrainpdf"+label+"_"+self.channel, param, param_mean,param_sigma);
            #    constrainpdf.Print();
            #    getattr(self.workspace4fit_,"import")(constrainpdf);
            #else:           
            #    param.setConstant(kTRUE);
            param=par.Next()
        return self.workspace4fit_.pdf("model%s_%s_mj"%(label,self.channel))

    ###################### ---------------------------------------------------
    def get_TTbar_mj_Model(self,label="_TTbar"):
        return self.get_General_mj_Model(label);
    ###################### ---------------------------------------------------
    def get_STop_mj_Model(self,label="_STop"):
        return self.get_General_mj_Model(label);
    ###################### ---------------------------------------------------
    def get_VV_mj_Model(self,label="_VV"):
        return self.get_General_mj_Model(label);

    ##################### ---------------------------------------------------
    def get_WJets_mj_Model(self,label):
        rdataset_WJets_mj=self.workspace4fit_.data("rdataset%s_%s_mj"%(label,self.channel))
        model_WJets=self.get_mj_Model(label);
        parameters_WJets=model_WJets.getParameters(rdataset_WJets_mj);
        par=parameters_WJets.createIterator(); par.Reset();
        param=par.Next()
        while (param):
            paraName=TString(param.GetName());
            #if not ( paraName.Contains("rrv_c_ErfExp_WJets") or paraName.Contains("rrv_number_WJets") or paraName.Contains("rrv_deltax")) :param.setConstant(kTRUE);
            #else: param.setConstant(0);
            if ( paraName.Contains("rrv_width_ErfExp_WJets") or paraName.Contains("rrv_offset_ErfExp_WJets") or paraName.Contains("rrv_p1_User1_WJets") or paraName.Contains("rrv_p1_User1_WJets")) :param.setConstant(kTRUE);
            else: param.setConstant(0);

            #param.setConstant(0);
            param=par.Next()
        return self.workspace4fit_.pdf("model%s_%s_mj"%(label,self.channel))

    ##################### ---------------------------------------------------
    def get_mlvj_Model(self,label, mlvj_region):
        return self.workspace4fit_.pdf("model"+label+mlvj_region+"_"+self.channel+"_mlvj");

    ##################### ---------------------------------------------------
    def get_General_mlvj_Model(self, label, mlvj_region="_signal_region"):
        rdataset_General_mlvj=self.workspace4fit_.data("rdataset%s%s_%s_mlvj"%(label, mlvj_region,self.channel))
        model_General=self.get_mlvj_Model(label,mlvj_region);
        model_General.Print()
        parameters_General=model_General.getParameters(rdataset_General_mlvj);
        par=parameters_General.createIterator(); par.Reset();
        param=par.Next()
        while (param):
            param.setConstant(kTRUE);
            param.Print();
            param=par.Next()
        return self.get_mlvj_Model(label,mlvj_region);

    ##################### ---------------------------------------------------
    def get_TTbar_mlvj_Model(self, mlvj_region="_signal_region"):
        return self.get_General_mlvj_Model("_TTbar",mlvj_region);
    ##################### ---------------------------------------------------
    def get_STop_mlvj_Model(self, mlvj_region="_signal_region"):
        return self.get_General_mlvj_Model("_STop",mlvj_region);

    ##################### ---------------------------------------------------
    def get_ggH_mlvj_Model(self, mlvj_region="_signal_region"):
        return self.get_General_mlvj_Model("_%s"%(self.higgs_sample),mlvj_region);

    ##################### ---------------------------------------------------
    def get_vbfH_mlvj_Model(self, mlvj_region="_signal_region"):
        return self.get_General_mlvj_Model("_%s"%(self.vbfhiggs_sample),mlvj_region);

    ##################### ---------------------------------------------------
    def get_VV_mlvj_Model(self, mlvj_region="_signal_region"):
        return self.get_General_mlvj_Model("_VV",mlvj_region);

    ##################### ---------------------------------------------------
    def get_WJets_mlvj_Model(self, mlvj_region="_signal_region"):
        print "get_WJets_mlvj_Model"
        rdataset_WJets_mlvj=self.workspace4fit_.data("rdataset_WJets%s_mlvj"%(mlvj_region))
        model_WJets=self.get_mlvj_Model("_WJets0",mlvj_region);
        model_WJets.Print()
        rdataset_WJets_mlvj.Print()
        parameters_WJets=model_WJets.getParameters(rdataset_WJets_mlvj);
        par=parameters_WJets.createIterator();
        par.Reset();
        param=par.Next()
        while (param):
            paraName=TString(param.GetName());
            param.Print();
            if paraName.Contains("rrv_number_WJets"): 
                if self.workspace4fit_.var("rrv_number_WJets_in_mj%s_from_fitting_%s"%(mlvj_region,self.channel)):
                    self.workspace4fit_.var("rrv_number_WJets_in_mj%s_from_fitting_%s"%(mlvj_region,self.channel)).Print()
                    param.setVal( self.workspace4fit_.var("rrv_number_WJets_in_mj%s_from_fitting_%s"%(mlvj_region,self.channel)).getVal() )
                if mlvj_region=="_signal_region": param.setConstant(kTRUE);
            param.Print();
            param=par.Next()
	    return self.get_mlvj_Model("_WJets0",mlvj_region);

    ##################### ---------------------------------------------------
    def fix_Model(self, label, mlvj_region="_signal_region",mass_spectrum="_mlvj"):
        rdataset=self.workspace4fit_.data("rdataset%s%s_%s%s"%(label,mlvj_region,self.channel,mass_spectrum))
        model=self.get_mlvj_Model(label,mlvj_region);
        parameters=model.getParameters(rdataset);
        par=parameters.createIterator(); par.Reset();
        param=par.Next()
        while (param):
            param.setConstant(kTRUE);
            param=par.Next()

    ##################### ---------------------------------------------------
    def fix_Pdf(self,model_pdf,argset_notparameter):
        model_pdf.Print()
        parameters=model_pdf.getParameters(argset_notparameter);
        par=parameters.createIterator(); par.Reset();
        param=par.Next()
        while (param):
            param.setConstant(kTRUE);
            param.Print();
            param=par.Next()

    ##################### ---------------------------------------------------
    def ShowParam_Pdf(self,model_pdf,argset_notparameter):
        model_pdf.Print()
        parameters=model_pdf.getParameters(argset_notparameter);
        par=parameters.createIterator(); par.Reset();
        param=par.Next()
        while (param):
            #param.Print();
            if not param.isConstant():
                if (param.getVal()-param.getMin())< param.getError()*1 or (param.getMax()- param.getVal())< param.getError()*1: 
                    #print param.getVal()-param.getMin(), param.getError()*2, (param.getMax()- param.getVal()); 
                    param.Print();
                    raw_input("ENTER");
            param=par.Next()


    def get_WJets_mlvj_correction_sb_lo_to_signal_region(self,label, mlvj_model):#exo-vv method: extract M_lvj shape of signal_region from sb_lo
        print "get_WJets_mlvj_correction_sb_lo_to_signal_region"
        rrv_x = self.workspace4fit_.var("rrv_mass_lvj"); 
        rdataset_WJets_sb_lo_mlvj=self.workspace4fit_.data("rdataset4fit%s_sb_lo_%s_mlvj"%(label,self.channel))
        rdataset_WJets_signal_region_mlvj=self.workspace4fit_.data("rdataset4fit%s_signal_region_%s_mlvj"%(label,self.channel))
        mplot = rrv_x.frame(RooFit.Title("correlation_pdf")); mplot.GetYaxis().SetTitle("alpha");

        if mlvj_model=="ErfExp_v1":
            rrv_c_sb     =self.workspace4fit_.var("rrv_c_ErfExp%s_sb_lo_%s"%(label,self.channel));
            rrv_offset_sb=self.workspace4fit_.var("rrv_offset_ErfExp%s_sb_lo_%s"%(label,self.channel));
            rrv_width_sb =self.workspace4fit_.var("rrv_width_ErfExp%s_sb_lo_%s"%(label,self.channel));
            rrv_delta_c = RooRealVar("rrv_delta_c_ErfExp%s_%s"%(label,self.channel),"rrv_delta_c_ErfExp%s_%s"%(label,self.channel),0., -100*rrv_c_sb.getError(),100*rrv_c_sb.getError()); 
            rrv_delta_offset = RooRealVar("rrv_delta_offset_ErfExp%s_%s"%(label,self.channel),"rrv_delta_offset_ErfExp%s_%s"%(label,self.channel),0., -100*rrv_offset_sb.getError(),100*rrv_offset_sb.getError()); 
            rrv_delta_width = RooRealVar("rrv_delta_width_ErfExp%s_%s"%(label,self.channel),"rrv_delta_width_ErfExp%s_%s"%(label,self.channel),0., -100*rrv_width_sb.getError(),100*rrv_width_sb.getError()); 
            rrv_c_sr =RooFormulaVar("rrv_c_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_c_sb, rrv_delta_c ) );
            rrv_offset_sr =RooFormulaVar("rrv_offset_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_offset_sb, rrv_delta_offset ) );
            rrv_width_sr =RooFormulaVar("rrv_width_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_width_sb, rrv_delta_width ) );
            correct_factor_pdf = RooAlpha("correct_factor_pdf","correct_factor_pdf", rrv_x, rrv_c_sr, rrv_offset_sr,rrv_width_sr, rrv_c_sb, rrv_offset_sb, rrv_width_sb, rrv_x.getMin(), rrv_x.getMax());
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);
        if mlvj_model=="ErfPow_v1":
            rrv_c_sb     =self.workspace4fit_.var("rrv_c_ErfPow%s_sb_lo_%s"%(label,self.channel));
            rrv_offset_sb=self.workspace4fit_.var("rrv_offset_ErfPow%s_sb_lo_%s"%(label,self.channel));
            rrv_width_sb =self.workspace4fit_.var("rrv_width_ErfPow%s_sb_lo_%s"%(label,self.channel));
            rrv_delta_c = RooRealVar("rrv_delta_c_ErfPow%s_%s"%(label,self.channel),"rrv_delta_c_ErfPow%s_%s"%(label,self.channel),0., -100*rrv_c_sb.getError(),100*rrv_c_sb.getError()); 
            rrv_delta_offset = RooRealVar("rrv_delta_offset_ErfPow%s_%s"%(label,self.channel),"rrv_delta_offset_ErfPow%s_%s"%(label,self.channel),0., -100*rrv_offset_sb.getError(),100*rrv_offset_sb.getError()); 
            rrv_delta_width = RooRealVar("rrv_delta_width_ErfPow%s_%s"%(label,self.channel),"rrv_delta_width_ErfPow%s_%s"%(label,self.channel),0., -100*rrv_width_sb.getError(),100*rrv_width_sb.getError()); 
            rrv_c_sr =RooFormulaVar("rrv_c_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_c_sb, rrv_delta_c ) );
            rrv_offset_sr =RooFormulaVar("rrv_offset_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_offset_sb, rrv_delta_offset ) );
            rrv_width_sr =RooFormulaVar("rrv_width_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_width_sb, rrv_delta_width ) );
            correct_factor_pdf = RooAlpha4ErfPowPdf("correct_factor_pdf","correct_factor_pdf", rrv_x, rrv_c_sr, rrv_offset_sr,rrv_width_sr, rrv_c_sb, rrv_offset_sb, rrv_width_sb);
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);
        if mlvj_model=="ErfPow2_v1":
            rrv_c0_sb     =self.workspace4fit_.var("rrv_c0_ErfPow2%s_sb_lo_%s"%(label,self.channel));
            rrv_c1_sb     =self.workspace4fit_.var("rrv_c1_ErfPow2%s_sb_lo_%s"%(label,self.channel));
            rrv_offset_sb=self.workspace4fit_.var("rrv_offset_ErfPow2%s_sb_lo_%s"%(label,self.channel));
            rrv_width_sb =self.workspace4fit_.var("rrv_width_ErfPow2%s_sb_lo_%s"%(label,self.channel));
            rrv_delta_c0 = RooRealVar("rrv_delta_c0_ErfPow2%s_%s"%(label,self.channel),"rrv_delta_c0_ErfPow2%s_%s"%(label,self.channel),-8, -20 ,0)#,0., -100*rrv_c0_sb.getError(),100*rrv_c0_sb.getError()); 
            rrv_delta_c1 = RooRealVar("rrv_delta_c1_ErfPow2%s_%s"%(label,self.channel),"rrv_delta_c1_ErfPow2%s_%s"%(label,self.channel),0., -5, 5);#-100*rrv_c1_sb.getError(),100*rrv_c1_sb.getError()); 
            rrv_delta_offset = RooRealVar("rrv_delta_offset_ErfPow2%s_%s"%(label,self.channel),"rrv_delta_offset_ErfPow2%s_%s"%(label,self.channel),30., 1.,80 );#0., -100*rrv_offset_sb.getError(),100*rrv_offset_sb.getError()); 
            rrv_delta_width = RooRealVar("rrv_delta_width_ErfPow2%s_%s"%(label,self.channel),"rrv_delta_width_ErfPow2%s_%s"%(label,self.channel),15,1.,100*rrv_width_sb.getError()); #0., -100*rrv_width_sb.getError(),100*rrv_width_sb.getError()); 
            rrv_c0_sr =RooFormulaVar("rrv_c0_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_c0_sb, rrv_delta_c0 ) );
            rrv_c1_sr =RooFormulaVar("rrv_c1_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_c1_sb, rrv_delta_c1 ) );
            rrv_offset_sr =RooFormulaVar("rrv_offset_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_offset_sb, rrv_delta_offset ) );
            rrv_width_sr =RooFormulaVar("rrv_width_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_width_sb, rrv_delta_width ) );
            correct_factor_pdf = RooAlpha4ErfPow2Pdf("correct_factor_pdf","correct_factor_pdf", rrv_x, rrv_c0_sr, rrv_c1_sr, rrv_offset_sr,rrv_width_sr, rrv_c0_sb, rrv_c1_sb, rrv_offset_sb, rrv_width_sb);
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);
        if mlvj_model=="ErfPowExp_v1":
            rrv_c0_sb     =self.workspace4fit_.var("rrv_c0_ErfPowExp%s_sb_lo_%s"%(label,self.channel));
            rrv_c1_sb     =self.workspace4fit_.var("rrv_c1_ErfPowExp%s_sb_lo_%s"%(label,self.channel));
            rrv_offset_sb=self.workspace4fit_.var("rrv_offset_ErfPowExp%s_sb_lo_%s"%(label,self.channel));
            rrv_width_sb =self.workspace4fit_.var("rrv_width_ErfPowExp%s_sb_lo_%s"%(label,self.channel));
            #rrv_delta_c0 = RooRealVar("rrv_delta_c0_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_c0_ErfPowExp%s_%s"%(label,self.channel),-8,-20,0); 
            #rrv_delta_c1 = RooRealVar("rrv_delta_c1_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_c1_ErfPowExp%s_%s"%(label,self.channel),0., -5,5 ); 
            #rrv_delta_offset = RooRealVar("rrv_delta_offset_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_offset_ErfPowExp%s_%s"%(label,self.channel),30,1,80); 
            #rrv_delta_width = RooRealVar("rrv_delta_width_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_width_ErfPowExp%s_%s"%(label,self.channel),15,1,100); 
            rrv_delta_c0 = RooRealVar("rrv_delta_c0_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_c0_ErfPowExp%s_%s"%(label,self.channel),
                    self.workspace4fit_.var("rrv_c0_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_c0_sb.getVal(),
                    self.workspace4fit_.var("rrv_c0_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_c0_sb.getVal()-4*rrv_c0_sb.getError(),
                    self.workspace4fit_.var("rrv_c0_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_c0_sb.getVal()+4*rrv_c0_sb.getError() )
            rrv_delta_c1 = RooRealVar("rrv_delta_c1_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_c1_ErfPowExp%s_%s"%(label,self.channel),
                    self.workspace4fit_.var("rrv_c1_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_c1_sb.getVal(),
                    self.workspace4fit_.var("rrv_c1_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_c1_sb.getVal()-4*rrv_c1_sb.getError(),
                    self.workspace4fit_.var("rrv_c1_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_c1_sb.getVal()+4*rrv_c1_sb.getError() )
            rrv_delta_offset = RooRealVar("rrv_delta_offset_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_offset_ErfPowExp%s_%s"%(label,self.channel),
                    self.workspace4fit_.var("rrv_offset_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_offset_sb.getVal(),
                    self.workspace4fit_.var("rrv_offset_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_offset_sb.getVal()-4*rrv_offset_sb.getError(),
                    self.workspace4fit_.var("rrv_offset_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_offset_sb.getVal()+4*rrv_offset_sb.getError() )
            rrv_delta_width = RooRealVar("rrv_delta_width_ErfPowExp%s_%s"%(label,self.channel),"rrv_delta_width_ErfPowExp%s_%s"%(label,self.channel),
                    self.workspace4fit_.var("rrv_width_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_width_sb.getVal(),
                    self.workspace4fit_.var("rrv_width_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_width_sb.getVal()-4*rrv_width_sb.getError(),
                    self.workspace4fit_.var("rrv_width_ErfPowExp%s_signal_region_%s"%(label,self.channel)).getVal()-rrv_width_sb.getVal()+4*rrv_width_sb.getError() )
            rrv_c0_sr =RooFormulaVar("rrv_c0_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_c0_sb, rrv_delta_c0 ) );
            rrv_c1_sr =RooFormulaVar("rrv_c1_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_c1_sb, rrv_delta_c1 ) );
            rrv_offset_sr =RooFormulaVar("rrv_offset_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_offset_sb, rrv_delta_offset ) );
            rrv_width_sr =RooFormulaVar("rrv_width_sr%s_%s"%(label,self.channel), "@0+@1",RooArgList(rrv_width_sb, rrv_delta_width ) );
            correct_factor_pdf = RooAlpha4ErfPowExpPdf("correct_factor_pdf","correct_factor_pdf", rrv_x, rrv_c0_sr, rrv_c1_sr, rrv_offset_sr,rrv_width_sr, rrv_c0_sb, rrv_c1_sb, rrv_offset_sb, rrv_width_sb);
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);
        if mlvj_model=="Exp":
            rrv_c_sb     =self.workspace4fit_.var("rrv_c_Exp%s_sb_lo_%s"%(label,self.channel));
            rrv_delta_c = RooRealVar("rrv_delta_c_Exp%s_%s"%(label,self.channel),"rrv_delta_c_Exp%s_%s"%(label,self.channel),0., -100*rrv_c_sb.getError(),100*rrv_c_sb.getError()); 
            correct_factor_pdf = RooExponential("correct_factor_pdf","correct_factor_pdf",rrv_x,rrv_delta_c);
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);
        if mlvj_model=="Pow":
            rrv_c_sb     =self.workspace4fit_.var("rrv_c_Pow%s_sb_lo_%s"%(label,self.channel));
            rrv_delta_c = RooRealVar("rrv_delta_c_Pow%s_%s"%(label,self.channel),"rrv_delta_c_Pow%s_%s"%(label,self.channel),0., -100*rrv_c_sb.getError(),100*rrv_c_sb.getError()); 
            correct_factor_pdf = RooPowPdf("correct_factor_pdf","correct_factor_pdf",rrv_x,rrv_delta_c);
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);
        if mlvj_model=="Pow2":
            rrv_c0_sb     =self.workspace4fit_.var("rrv_c0_Pow2%s_sb_lo_%s"%(label,self.channel));
            rrv_c1_sb     =self.workspace4fit_.var("rrv_c1_Pow2%s_sb_lo_%s"%(label,self.channel));
            rrv_delta_c0 = RooRealVar("rrv_delta_c0_Pow2%s_%s"%(label,self.channel),"rrv_delta_c0_Pow2%s_%s"%(label,self.channel),0., -100*rrv_c0_sb.getError(),100*rrv_c0_sb.getError()); 
            rrv_delta_c1 = RooRealVar("rrv_delta_c1_Pow2%s_%s"%(label,self.channel),"rrv_delta_c1_Pow2%s_%s"%(label,self.channel),0., -100*rrv_c1_sb.getError(),100*rrv_c1_sb.getError()); 
            correct_factor_pdf = RooPow2Pdf("correct_factor_pdf","correct_factor_pdf",rrv_x,rrv_delta_c0,rrv_delta_c1);
            #getattr(self.workspace4fit_,"import")(correct_factor_pdf);


        model_pdf_sb_lo_WJets         = self.workspace4fit_.pdf("model_pdf%s_sb_lo_%s_mlvj"%(label,self.channel));
        model_pdf_signal_region_WJets = RooProdPdf("model_pdf%s_signal_region_%s_mlvj"%(label,self.channel),"model_pdf%s_signal_region_%s_mlvj"%(label,self.channel) ,model_pdf_sb_lo_WJets,correct_factor_pdf);

        data_category=RooCategory("data_category","data_category");
        data_category.defineType("sideband");
        data_category.defineType("signal_region");
        combData4fit=self.workspace4fit_.data("combData4fit%s_%s"%(label,self.channel));
        simPdf=RooSimultaneous("simPdf","simPdf",data_category);
        simPdf.addPdf(model_pdf_sb_lo_WJets,"sideband");
        simPdf.addPdf(model_pdf_signal_region_WJets,"signal_region");
        rfresult=simPdf.fitTo(combData4fit,RooFit.Save(kTRUE), RooFit.SumW2Error(kTRUE));
        rfresult=simPdf.fitTo(combData4fit,RooFit.Save(kTRUE), RooFit.SumW2Error(kTRUE));
        rfresult.Print();
        rfresult.covarianceMatrix().Print(); #raw_input("ENTER");

        wsfit_tmp=RooWorkspace("wsfit_tmp%s_sim_mlvj"%(label));
        Deco=PdfDiagonalizer("Deco%s_sim_%s_mlvj"%(label,self.channel),wsfit_tmp,rfresult);
        correct_factor_pdf_deco=Deco.diagonalize(correct_factor_pdf);
        correct_factor_pdf_deco.Print();
        correct_factor_pdf_deco.getParameters(rdataset_WJets_signal_region_mlvj).Print("v");
        getattr(self.workspace4fit_,"import")(correct_factor_pdf_deco);
        if label=="_WJets0":
            mplot_sb_lo = rrv_x.frame(RooFit.Title("WJets sb low"));
            rdataset_WJets_sb_lo_mlvj.plotOn(mplot_sb_lo);
            model_pdf_sb_lo_WJets.plotOn(mplot_sb_lo);
            hpull=mplot_sb_lo.pullHist();
            mplot_pull_sideband = rrv_x.frame(RooFit.Title("Pull Distribution"));
            mplot_pull_sideband.addPlotable(hpull,"P");
            mplot_pull_sideband.SetTitle("PULL");
            mplot_pull_sideband.GetYaxis().SetRangeUser(-5,5);
            parameters_list=model_pdf_sb_lo_WJets.getParameters(rdataset_WJets_sb_lo_mlvj);
            self.draw_canvas( mplot_sb_lo, mplot_pull_sideband,parameters_list,"plots_%s_%s/other/"%(self.channel,self.PS_model), "m_lvj%s_sb_lo_sim"%(label),"",1,0)

            mplot_signal_region = rrv_x.frame(RooFit.Title("WJets sr"));
            rdataset_WJets_signal_region_mlvj.plotOn(mplot_signal_region);
            model_pdf_signal_region_WJets.plotOn(mplot_signal_region);
            hpull=mplot_signal_region.pullHist();
            mplot_pull_signal_region = rrv_x.frame(RooFit.Title("Pull Distribution"));
            mplot_pull_signal_region.addPlotable(hpull,"P");
            mplot_pull_signal_region.SetTitle("PULL");
            mplot_pull_signal_region.GetYaxis().SetRangeUser(-5,5);
            parameters_list=model_pdf_signal_region_WJets.getParameters(rdataset_WJets_signal_region_mlvj);
            self.draw_canvas( mplot_signal_region, mplot_pull_signal_region,parameters_list,"plots_%s_%s/other/"%(self.channel,self.PS_model), "m_lvj%s_signal_region_sim"%(label),"",1,0);

        model_pdf_sb_lo_WJets.plotOn(mplot,RooFit.Name("Sideband"));
        model_pdf_signal_region_WJets.plotOn(mplot, RooFit.LineColor(kRed) ,RooFit.Name("Signal Region"));
        correct_factor_pdf_deco.plotOn(mplot, RooFit.LineColor(kBlack),RooFit.Name("#alpha") );
        if label=="_WJets0":
            if self.workspace4fit_.pdf("correct_factor_pdf_Deco_WJets1_sim_%s_mlvj"%(self.channel)):
                self.workspace4fit_.pdf("correct_factor_pdf_Deco_WJets1_sim_%s_mlvj"%(self.channel)).plotOn(mplot, RooFit.LineColor(kMagenta), RooFit.LineStyle(3),RooFit.Name("#alpha: Alter PS") ); 
            if self.workspace4fit_.pdf("correct_factor_pdf_Deco_WJets01_sim_%s_mlvj"%(self.channel)):
                self.workspace4fit_.pdf("correct_factor_pdf_Deco_WJets01_sim_%s_mlvj"%(self.channel)).plotOn(mplot, RooFit.LineColor(kOrange), RooFit.LineStyle(7),RooFit.Name("#alpha: Alter Function") ); 

        paras=RooArgList();
        if mlvj_model=="ErfExp_v1" or mlvj_model=="ErfPow_v1" :
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig0"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig1"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig2"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig3"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig4"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig5"%(label,self.channel) ));
        if mlvj_model=="ErfPow2_v1" or mlvj_model=="ErfPowExp_v1" :
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig0"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig1"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig2"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig3"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig4"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig5"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig6"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig7"%(label,self.channel) ));
        if mlvj_model=="Exp" or mlvj_model=="Pow":
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig0"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig1"%(label,self.channel) ));
        if mlvj_model=="Pow2":
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig0"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig1"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig2"%(label,self.channel) ));
            paras.add(self.workspace4fit_.var("Deco%s_sim_%s_mlvj_eig3"%(label,self.channel) ));
        if label=="_WJets0":
            draw_error_band_shape_Decor("correct_factor_pdf_Deco%s_sim_%s_mlvj"%(label,self.channel),"rrv_mass_lvj", paras, self.workspace4fit_,1 ,mplot,6,"F","#alpha #pm",20,400);
            draw_error_band_shape_Decor("correct_factor_pdf_Deco%s_sim_%s_mlvj"%(label,self.channel),"rrv_mass_lvj", paras, self.workspace4fit_,2 ,mplot,6,"F","#alpha #pm",20,400);
        leg=self.legend4Plot(mplot,0);mplot.addObject(leg);

        #mplot.GetYaxis().SetRangeUser(0,mplot.GetMaximum()*1.1);
        if self.higgs_sample=="ggH600" or self.higgs_sample=="ggH700":
            mplot.GetYaxis().SetRangeUser(0,0.25);
        else: 
            mplot.GetYaxis().SetRangeUser(0,0.28);
 
        self.draw_canvas1(mplot,"plots_%s_%s/other/"%(self.channel,self.PS_model),"correction_pdf%s_%s_%s_M_lvj_signal_region_to_sideband"%(label,self.PS_model,self.MODEL_4_mlvj),0,0);

        correct_factor_pdf_deco.getParameters(rdataset_WJets_sb_lo_mlvj).Print("v");

        model_pdf_WJets_sb_lo_from_fitting_mlvj_Deco=self.workspace4fit_.pdf("model_pdf%s_sb_lo_from_fitting_%s_mlvj_Deco%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel,label, self.channel));
        model_pdf_WJets_sb_lo_from_fitting_mlvj_Deco.Print("v");

        model_pdf_WJets_signal_region_after_correct_mlvj=RooProdPdf("model_pdf%s_signal_region_%s_after_correct_mlvj"%(label,self.channel),"model_pdf%s_signal_region_%s_after_correct_mlvj"%(label,self.channel),model_pdf_WJets_sb_lo_from_fitting_mlvj_Deco,self.workspace4fit_.pdf("correct_factor_pdf_Deco%s_sim_%s_mlvj"%(label,self.channel)) );
        model_pdf_WJets_signal_region_after_correct_mlvj.Print()
        self.fix_Pdf(model_pdf_WJets_signal_region_after_correct_mlvj,RooArgSet(rrv_x))
        getattr(self.workspace4fit_,"import")(model_pdf_WJets_signal_region_after_correct_mlvj)

        #calculate the normalization and alpha for limit datacard
        self.workspace4fit_.var("rrv_number%s_signal_region_%s_mlvj"%(label,self.channel)).Print();
        self.workspace4fit_.var("rrv_number%s_in_mj_signal_region_from_fitting_%s"%(label,self.channel)).Print();
        self.workspace4fit_.var("rrv_number%s_signal_region_%s_mlvj"%(label,self.channel)).setVal(self.workspace4fit_.var("rrv_number%s_in_mj_signal_region_from_fitting_%s"%(label,self.channel)).getVal());
        self.workspace4fit_.var("rrv_number%s_signal_region_%s_mlvj"%(label,self.channel)).setError(self.workspace4fit_.var("rrv_number%s_in_mj_signal_region_from_fitting_%s"%(label,self.channel)).getError());

        self.workspace4fit_.var("rrv_number%s_signal_region_%s_mlvj"%(label,self.channel)).setConstant(kTRUE);

    ############# ---------------------------------------------------
    def fit_mj_single_MC(self,in_file_name, label, in_model_name, addtionimform=""):
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j"); 
        rdataset_mj = self.workspace4fit_.data("rdataset4fit"+label+"_"+self.channel+"_mj"); 
        rdataset_mj.Print();

        model = self.make_Model(label,in_model_name);
        rfresult = model.fitTo(rdataset_mj,RooFit.Save(1),RooFit.Extended(kTRUE) );
        rfresult = model.fitTo(rdataset_mj,RooFit.Save(1), RooFit.SumW2Error(kTRUE) ,RooFit.Extended(kTRUE) );
        rfresult = model.fitTo(rdataset_mj,RooFit.Save(1), RooFit.SumW2Error(kTRUE) ,RooFit.Extended(kTRUE) );

        mplot = rrv_mass_j.frame(RooFit.Title(label+" fitted by "+in_model_name));
        rdataset_mj.plotOn( mplot ,RooFit.DataError(RooAbsData.SumW2));
        #model.plotOn(mplot,RooFit.VisualizeError(rfresult,1,kFALSE),RooFit.DrawOption("F"),RooFit.FillColor(kOrange), RooFit.VLines());
        #draw_error_band(rdataset_mj, model,self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj") ,rfresult,mplot,6,"L");
        draw_error_band_extendPdf(rdataset_mj, model, rfresult,mplot,6,"L");
        rdataset_mj.plotOn( mplot ,RooFit.DataError(RooAbsData.SumW2) );
        model.plotOn( mplot , RooFit.VLines());

        #pull
        hpull=mplot.pullHist();
        mplot_pull = rrv_mass_j.frame(RooFit.Title("Pull Distribution"));
        mplot_pull.addPlotable(hpull,"P");
        mplot_pull.SetTitle("PULL");
        mplot_pull.GetYaxis().SetRangeUser(-5,5);
         
        parameters_list=model.getParameters(rdataset_mj);
        mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1);
        self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_j_fitting%s_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, addtionimform, self.wtagger_label, self.nPV_min, self.nPV_max), label+in_file_name, in_model_name)
        rfresult.Print(); 
        #rfresult.covarianceMatrix().Print(); #raw_input("ENTER"); 
        
        #normalize the number of total events to lumi
        self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").setVal( self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").getVal()*self.workspace4fit_.var("rrv_scale_to_lumi"+label+"_"+self.channel).getVal()  )
        self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").setError(self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").getError()*self.workspace4fit_.var("rrv_scale_to_lumi"+label+"_"+self.channel).getVal()  )
        if TString(label).Contains("ggH"):
            self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").setVal( self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").getVal()  )
            self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").setError(self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").getError() )
        self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj").Print();

    ############# ---------------------------------------------------
    def fit_mj_singlebackground_MC_TTbar_controlsample(self,in_file_name, label, in_model_name):
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j"); 
        rdataset_mj = self.workspace4fit_.data("rdataset4fit"+label+"_"+self.channel+"_mj"); 
        model = self.make_Model(label,in_model_name);
        rfresult = model.fitTo(rdataset_mj,RooFit.Save(1), RooFit.SumW2Error(kTRUE) ,RooFit.Extended(kTRUE), RooFit.Range("controlsample_fitting_range") );
        rfresult = model.fitTo(rdataset_mj,RooFit.Save(1), RooFit.SumW2Error(kTRUE) ,RooFit.Extended(kTRUE), RooFit.Range("controlsample_fitting_range") );
        
        mplot = rrv_mass_j.frame(RooFit.Title(label+" fitted by "+in_model_name));
        rdataset_mj.plotOn( mplot ,RooFit.DataError(RooAbsData.SumW2) );
        model.plotOn( mplot, RooFit.VisualizeError(rfresult,1),RooFit.FillColor(kOrange) , RooFit.VLines(),RooFit.NormRange("controlsample_fitting_range"));
        #model.plotOn(mplot,RooFit.VisualizeError(rfresult,1,kFALSE),RooFit.DrawOption("F"),RooFit.FillColor(kOrange), RooFit.VLines(),RooFit.NormRange("controlsample_fitting_range"));
        model.plotOn( mplot , RooFit.VLines(),RooFit.NormRange("controlsample_fitting_range"));
        model.plotOn( mplot, RooFit.Components("erfExp"+label+"_"+self.channel), RooFit.LineStyle(kDashed),RooFit.LineColor(kGreen) , RooFit.VLines(),RooFit.NormRange("controlsample_fitting_range"));
        model.plotOn( mplot, RooFit.Components("gaus"+label+"_"+self.channel), RooFit.LineStyle(kDashed),RooFit.LineColor(kRed) , RooFit.VLines(),RooFit.NormRange("controlsample_fitting_range"));
        model.plotOn( mplot , RooFit.VLines(),RooFit.NormRange("controlsample_fitting_range"));
        rdataset_mj.plotOn( mplot ,RooFit.DataError(RooAbsData.SumW2) );
        #pull
        hpull=mplot.pullHist();
        mplot_pull = rrv_mass_j.frame(RooFit.Title("Pull Distribution"));
        mplot_pull.addPlotable(hpull,"P");
        mplot_pull.SetTitle("PULL");
        mplot_pull.GetYaxis().SetRangeUser(-5,5);
         
        parameters_list=model.getParameters(rdataset_mj);
        mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1);
        self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max), label+in_file_name, in_model_name)
        rfresult.Print();

    ############# ---------------------------------------------------
    def change_dataset_to_histpdf(self, x,dataset):
        datahist=dataset.binnedClone(dataset.GetName()+"_binnedClone",dataset.GetName()+"_binnedClone")
        histpdf=RooHistPdf(dataset.GetName()+"_histpdf",dataset.GetName()+"_histpdf",RooArgSet(x),datahist)
        getattr(self.workspace4fit_,"import")(histpdf)

    ############# ---------------------------------------------------
    def change_dataset_to_histogram(self, x,dataset,label=""):
        datahist=dataset.binnedClone(dataset.GetName()+"_binnedClone",dataset.GetName()+"_binnedClone")
        binswidth=5.;
        nbin=int( (x.getMax()-x.getMin())/binswidth );
        if label=="":
            return datahist.createHistogram("histo_%s"%(dataset.GetName()),x, RooFit.Binning( nbin ,x.getMin(),x.getMax()));
        else:
            return datahist.createHistogram("histo_"+label,x, RooFit.Binning( nbin,x.getMin(),x.getMax()));

    ############# ---------------------------------------------------
    def fit_mj_TTbar_controlsample(self,in_file_name):
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");# rrv_mass_j.setBins(40)
        rdataset_data_mj = self.workspace4fit_.data("rdataset_data_"+self.channel+"_mj"); 
        rdataset_TTbar_mj = self.workspace4fit_.data("rdataset_TTbar_"+self.channel+"_mj"); 
        rdataset_TTbar_mj.Print();
        rdataset_STop_mj = self.workspace4fit_.data("rdataset_STop_"+self.channel+"_mj"); 
        rdataset_VV_mj = self.workspace4fit_.data("rdataset_VV_"+self.channel+"_mj"); 
        rdataset_WJets_mj = self.workspace4fit_.data("rdataset_WJets0_"+self.channel+"_mj"); 
        rdataset_TotalMC_mj= rdataset_TTbar_mj.Clone("rdataset_TotalMC_"+self.channel+"_mj");
        rdataset_TotalMC_mj.append(rdataset_STop_mj);
        rdataset_TotalMC_mj.append(rdataset_VV_mj);
        rdataset_TotalMC_mj.append(rdataset_WJets_mj);

        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_TTbar_mj);
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_STop_mj)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_VV_mj)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_WJets_mj)
        model_pdf_TTbar= self.workspace4fit_.pdf(rdataset_TTbar_mj.GetName()+"_histpdf")
        model_pdf_STop = self.workspace4fit_.pdf(rdataset_STop_mj.GetName()+"_histpdf")
        model_pdf_VV   = self.workspace4fit_.pdf(rdataset_VV_mj.GetName()+"_histpdf")
        model_pdf_WJets   = self.workspace4fit_.pdf(rdataset_WJets_mj.GetName()+"_histpdf")
        number_STop =RooRealVar("rrv_number_STop" ,"rrv_number_STop",rdataset_STop_mj.sumEntries());
        number_VV   =RooRealVar("rrv_number_VV"   ,"rrv_number_VV",rdataset_VV_mj.sumEntries());
        number_WJets=RooRealVar("rrv_number_WJets","rrv_number_WJets",rdataset_WJets_mj.sumEntries());
        model_STop =RooExtendPdf("model_STop","model_STop",model_pdf_STop,number_STop)
        model_VV   =RooExtendPdf("model_VV","model_VV",model_pdf_VV,number_VV)
        model_WJets=RooExtendPdf("model_WJets","model_WJets",model_pdf_WJets,number_WJets)
        scale_number_STop =rdataset_STop_mj.sumEntries()/rdataset_data_mj.sumEntries()
        scale_number_TTbar=rdataset_TTbar_mj.sumEntries()/rdataset_data_mj.sumEntries()
        scale_number_VV   =rdataset_VV_mj.sumEntries()/rdataset_data_mj.sumEntries()
        scale_number_WJets=rdataset_WJets_mj.sumEntries()/rdataset_data_mj.sumEntries()

        #self.with_tau2tau1
        model_ttbar_data = self.make_Model("_ttbar_data","2Gaus_ttbar_"+self.with_tau2tau1);
        model_bkg_data = self.make_Model("_bkg_data","ErfExp_ttbar_"+self.with_tau2tau1);
        model_ttbar_TotalMC = self.make_Model("_ttbar_TotalMC","2Gaus_ttbar_"+self.with_tau2tau1);
        model_bkg_TotalMC = self.make_Model("_bkg_TotalMC","ErfExp_ttbar_"+self.with_tau2tau1);
        model_data=RooAddPdf("model_data","model_data", RooArgList(model_ttbar_data, model_bkg_data));
        model_TotalMC=RooAddPdf("model_TotalMC","model_TotalMC", RooArgList(model_ttbar_TotalMC, model_bkg_TotalMC));

        if self.with_tau2tau1=="with_tau2tau1" and self.channel=="mu":
            self.workspace4fit_.var("rrv_number_ttbar_data"+"_"+self.channel+"_mj").setMax(1261.87);
            self.workspace4fit_.var("rrv_number_ttbar_TotalMC"+"_"+self.channel+"_mj").setMax(1271.02);
        elif self.with_tau2tau1=="with_tau2tau1" and self.channel=="el":
            self.workspace4fit_.var("rrv_number_ttbar_data"+"_"+self.channel+"_mj").setMax(993.39 );
            self.workspace4fit_.var("rrv_number_ttbar_TotalMC"+"_"+self.channel+"_mj").setMax(1047.53);


        model_data.fitTo(rdataset_data_mj,RooFit.Save(1), RooFit.Extended(kTRUE) , RooFit.Range("controlsample_fitting_range") );
        rfresult_data = model_data.fitTo(rdataset_data_mj,RooFit.Save(1), RooFit.Extended(kTRUE) , RooFit.Range("controlsample_fitting_range") );

        model_TotalMC.fitTo(rdataset_TotalMC_mj, RooFit.SumW2Error(kTRUE),RooFit.Save(1), RooFit.Extended(kTRUE), RooFit.Range("controlsample_fitting_range") );
        rfresult_TotalMC =model_TotalMC.fitTo(rdataset_TotalMC_mj, RooFit.SumW2Error(kTRUE),RooFit.Save(1), RooFit.Extended(kTRUE), RooFit.Range("controlsample_fitting_range") );
        rfresult_TotalMC =model_TotalMC.fitTo(rdataset_TotalMC_mj,RooFit.Save(1), RooFit.Extended(kTRUE), RooFit.Range("controlsample_fitting_range") );
        scale_number_TotalMC=rdataset_TotalMC_mj.sumEntries()/rdataset_data_mj.sumEntries()
        
        mplot = rrv_mass_j.frame();

        rdataset_data_mj.plotOn( mplot, RooFit.Invisible() );

        model_pdf_WJets.plotOn(mplot,RooFit.Normalization(scale_number_WJets),RooFit.Name("WJets_invisible"),RooFit.Invisible(), RooFit.VLines())
        model_pdf_VV.plotOn(mplot,RooFit.Normalization(scale_number_VV),RooFit.Name("VV_invisible"), RooFit.AddTo("WJets_invisible"),RooFit.Invisible(), RooFit.VLines())
        model_pdf_STop.plotOn(mplot,RooFit.Normalization(scale_number_STop),RooFit.Name("STop_invisible"), RooFit.AddTo("VV_invisible"),RooFit.Invisible(), RooFit.VLines())
        model_pdf_TTbar.plotOn(mplot,RooFit.Normalization(scale_number_TTbar),RooFit.Name("TTbar_invisible"), RooFit.AddTo("STop_invisible"),RooFit.Invisible(), RooFit.VLines())
        model_pdf_TTbar.plotOn(mplot,RooFit.Normalization(scale_number_TTbar),RooFit.Name("TTbar"), RooFit.AddTo("STop_invisible"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines())
        model_pdf_STop.plotOn(mplot,RooFit.Normalization(scale_number_STop),RooFit.Name("STop"), RooFit.AddTo("VV_invisible"), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines())
        model_pdf_VV.plotOn(mplot,RooFit.Normalization(scale_number_VV),RooFit.Name("VV"), RooFit.AddTo("WJets_invisible"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines())
        model_pdf_WJets.plotOn(mplot,RooFit.Normalization(scale_number_WJets),RooFit.Name("WJets"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines())

        rdataset_data_mj.plotOn( mplot,RooFit.Name("data") );
        if self.wtagger_cut<10:
            model_TotalMC.plotOn( mplot,RooFit.Normalization(scale_number_TotalMC) ,RooFit.Name("MC fit") ,RooFit.NormRange("controlsample_fitting_range") , RooFit.LineStyle(kDashed));
            model_TotalMC.plotOn( mplot,RooFit.Normalization(scale_number_TotalMC) ,RooFit.Name("MC fit comp") ,RooFit.NormRange("controlsample_fitting_range") , RooFit.Components("model_pdf_bkg_TotalMC_%s_mj"%(self.channel)),  RooFit.LineStyle(kDashed), RooFit.LineColor(kRed) );
            model_data.plotOn( mplot,RooFit.Name("data fit"), RooFit.NormRange("controlsample_fitting_range") );
            model_data.plotOn( mplot,RooFit.Name("data fit comp"), RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("model_pdf_bkg_data_%s_mj"%(self.channel)), RooFit.LineColor(kRed) );
            model_data.plotOn( mplot,RooFit.Name("data fit invisi"), RooFit.NormRange("controlsample_fitting_range") );
        leg=self.legend4Plot(mplot,0)
        mplot.addObject(leg)

        #add mean and width to mplot
        parameters_list=model_data.getParameters(rdataset_data_mj);
        parameters_list.add( model_TotalMC.getParameters(rdataset_data_mj))
        rrv_mean_gaus_data=parameters_list.find("rrv_mean1_gaus_ttbar_data"+"_"+self.channel);
        rrv_sigma_gaus_data=parameters_list.find("rrv_sigma1_gaus_ttbar_data"+"_"+self.channel);
        rrv_mean_gaus_TotalMC=parameters_list.find("rrv_mean1_gaus_ttbar_TotalMC"+"_"+self.channel);
        rrv_sigma_gaus_TotalMC=parameters_list.find("rrv_sigma1_gaus_ttbar_TotalMC"+"_"+self.channel);
        tl_MC_mean   =TLatex(0.65 ,0.42, ("Mean_{MC  } = %3.1f #pm %2.1f")%(rrv_mean_gaus_TotalMC.getVal(), rrv_mean_gaus_TotalMC.getError()) );
        tl_MC_sigma  =TLatex(0.65 ,0.37, ("Sigma_{MC  }= %2.1f #pm %2.1f")%(rrv_sigma_gaus_TotalMC.getVal(), rrv_sigma_gaus_TotalMC.getError()) );
        #tl_data_mean =TLatex(0.65 ,0.32, ("Mean_{data} = %3.1f #pm %2.1f")%(rrv_mean_gaus_data.getVal(), rrv_mean_gaus_data.getError()) );
        tl_data_mean =TLatex(0.65 ,0.32, ("Mean_{data} = %3.1f #pm %2.1f")%(rrv_mean_gaus_data.getVal(), 0.6 ) );
        tl_data_sigma=TLatex(0.65 ,0.27, ("Sigma_{data}= %2.1f #pm %2.1f")%(rrv_sigma_gaus_data.getVal(), rrv_sigma_gaus_data.getError()) );
        tl_MC_mean.SetNDC(); tl_MC_sigma.SetNDC(); tl_data_mean.SetNDC(); tl_data_sigma.SetNDC();
        tl_data_mean.SetTextSize(0.03)
        tl_data_sigma.SetTextSize(0.03)
        tl_MC_mean.SetTextSize(0.03)
        tl_MC_sigma.SetTextSize(0.03)
        if self.wtagger_cut<10:
            mplot.addObject(tl_data_mean);
            mplot.addObject(tl_data_sigma);
            mplot.addObject(tl_MC_mean);
            mplot.addObject(tl_MC_sigma);
      
        #signal window
        lowerLine = TLine(self.mj_signal_min,0.,self.mj_signal_min,mplot.GetMaximum()); lowerLine.SetLineWidth(2); lowerLine.SetLineColor(kGray+2); lowerLine.SetLineStyle(9);
        upperLine = TLine(self.mj_signal_max,0.,self.mj_signal_max,mplot.GetMaximum()); upperLine.SetLineWidth(2); upperLine.SetLineColor(kGray+2); upperLine.SetLineStyle(9);
        mplot.addObject(lowerLine);
        mplot.addObject(upperLine);
        #pull
        hpull=mplot.pullHist();
        mplot_pull = rrv_mass_j.frame(RooFit.Title("Pull Distribution"));
        mplot_pull.addPlotable(hpull,"P");
        mplot_pull.SetTitle("PULL");
        mplot_pull.GetYaxis().SetRangeUser(-5,5);
         
        mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1);
        self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max), in_file_name, "ErfExp2Gaus"+"Total"+self.with_tau2tau1)
        self.draw_canvas1(mplot,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max),"control_%s_%s_%s"%(self.wtagger_label,self.channel,self.with_tau2tau1));
        
        #calculate the mva eff
        rrv_number_ttbar_data=parameters_list.find("rrv_number_ttbar_data"+"_"+self.channel+"_mj");
        rrv_number_ttbar_TotalMC=parameters_list.find("rrv_number_ttbar_TotalMC"+"_"+self.channel+"_mj");
        rrv_number_ttbar_data.Print();
        rrv_number_ttbar_TotalMC.Print();

        # to calculate the TTbar's normalization and error in M_J signal_region. The error must contain the shape error
        fullInt_data   = model_ttbar_data.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j) );
        signalInt_data = model_ttbar_data.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("signal_region"));
        fullInt_val_data=fullInt_data.getVal()
        signalInt_val_data=signalInt_data.getVal()/fullInt_val_data
        rrv_number_TTbar_in_mj_signal_region_from_fitting_data=RooRealVar("rrv_number_TTbar_in_mj_signal_region_from_fitting_data_%s"%(self.channel),"rrv_number_TTbar_in_mj_signal_region_from_fitting_data_%s"%(self.channel),rrv_number_ttbar_data.getVal()*signalInt_val_data);
        #error
        rrv_number_TTbar_in_mj_signal_region_from_fitting_data.setError( Calc_error_extendPdf(rdataset_data_mj, model_ttbar_data, rfresult_data,"signal_region") );
        rrv_number_TTbar_in_mj_signal_region_from_fitting_data.Print();
        #getattr(self.workspace4fit_,"import")(rrv_number_WJets_in_mj_signal_region_from_fitting);
        fullInt_TotalMC   = model_ttbar_TotalMC.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j) );
        signalInt_TotalMC = model_ttbar_TotalMC.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("signal_region"));
        fullInt_val_TotalMC=fullInt_TotalMC.getVal()
        signalInt_val_TotalMC=signalInt_TotalMC.getVal()/fullInt_val_TotalMC
        rrv_number_TTbar_in_mj_signal_region_from_fitting_TotalMC=RooRealVar("rrv_number_TTbar_in_mj_signal_region_from_fitting_TotalMC_%s"%(self.channel),"rrv_number_TTbar_in_mj_signal_region_from_fitting_TotalMC_%s"%(self.channel),rrv_number_ttbar_TotalMC.getVal()*signalInt_val_TotalMC);
        #error
        rrv_number_TTbar_in_mj_signal_region_from_fitting_TotalMC.setError( Calc_error_extendPdf(rdataset_TotalMC_mj, model_ttbar_TotalMC, rfresult_TotalMC,"signal_region") );
        rrv_number_TTbar_in_mj_signal_region_from_fitting_TotalMC.Print();
        #getattr(self.workspace4fit_,"import")(rrv_number_WJets_in_mj_signal_region_from_fitting);
        print "number in signal region"
        rrv_number_TTbar_in_mj_signal_region_from_fitting_data.Print();
        rrv_number_TTbar_in_mj_signal_region_from_fitting_TotalMC.Print();



        #self.workspace4fit_.var("rrv_number_dataset_signal_region_data_"+self.channel+"_mj").Print()
        #self.workspace4fit_.var("rrv_number_dataset_signal_region_VV_"+self.channel+"_mj").Print()
        #self.workspace4fit_.var("rrv_number_dataset_signal_region_WJets0_"+self.channel+"_mj").Print()
        #self.workspace4fit_.var("rrv_number_dataset_signal_region_STop_"+self.channel+"_mj").Print()
        #self.workspace4fit_.var("rrv_number_dataset_signal_region_TTbar_"+self.channel+"_mj").Print()

        #number_dataset_signal_region_data_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_data_"+self.channel+"_mj").getVal();
        #number_dataset_signal_region_error2_data_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_error2_data_"+self.channel+"_mj").getVal();
        #print "event number of data in signal_region: %s +/- sqrt(%s)"%(number_dataset_signal_region_data_mj, number_dataset_signal_region_error2_data_mj);
        #self.file_out_ttbar_control.write("event number of data in signal_region: %s +/- sqrt(%s)\n"%(number_dataset_signal_region_data_mj, number_dataset_signal_region_error2_data_mj));
        #number_dataset_signal_region_pseudodata_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_pseudodata_"+self.channel+"_mj").getVal();
        #number_dataset_signal_region_error2_pseudodata_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_error2_pseudodata_"+self.channel+"_mj").getVal();
        #print "event number of pseudodata in signal_region: %s +/- sqrt(%s) "%(number_dataset_signal_region_pseudodata_mj, number_dataset_signal_region_error2_pseudodata_mj);
        #self.file_out_ttbar_control.write("event number of pseudodata in signal_region: %s +/- sqrt(%s) \n"%(number_dataset_signal_region_pseudodata_mj, number_dataset_signal_region_error2_pseudodata_mj));


        #number_dataset_signal_region_before_mva_data_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_before_mva_data_"+self.channel+"_mj").getVal();
        #number_dataset_signal_region_before_mva_error2_data_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_before_mva_error2_data_"+self.channel+"_mj").getVal();
        #print "event number of data in signal_region before_mva: %s +/- sqrt(%s)"%(number_dataset_signal_region_before_mva_data_mj, number_dataset_signal_region_before_mva_error2_data_mj);
        #self.file_out_ttbar_control.write("event number of data in signal_region before_mva: %s +/- sqrt(%s)\n"%(number_dataset_signal_region_before_mva_data_mj, number_dataset_signal_region_before_mva_error2_data_mj));

        #number_dataset_signal_region_before_mva_pseudodata_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_before_mva_pseudodata_"+self.channel+"_mj").getVal();
        #number_dataset_signal_region_before_mva_error2_pseudodata_mj=self.workspace4fit_.var("rrv_number_dataset_signal_region_before_mva_error2_pseudodata_"+self.channel+"_mj").getVal();
        #print "event number of pseudodata in signal_region before_mva: %s +/- sqrt(%s) "%(number_dataset_signal_region_before_mva_pseudodata_mj, number_dataset_signal_region_before_mva_error2_pseudodata_mj);
        #self.file_out_ttbar_control.write("event number of pseudodata in signal_region before_mva: %s +/- sqrt(%s) \n"%(number_dataset_signal_region_before_mva_pseudodata_mj, number_dataset_signal_region_before_mva_error2_pseudodata_mj));

        ## wtagger_eff reweight: only reweight the efficiency difference between MC and data
        #wtagger_eff_MC  = number_dataset_signal_region_pseudodata_mj/number_dataset_signal_region_before_mva_pseudodata_mj;
        #wtagger_eff_data= number_dataset_signal_region_data_mj/number_dataset_signal_region_before_mva_data_mj;

        #wtagger_eff_reweight=wtagger_eff_data/wtagger_eff_MC;
        #wtagger_eff_reweight_err=wtagger_eff_reweight*TMath.Sqrt(
        #        number_dataset_signal_region_error2_data_mj/number_dataset_signal_region_data_mj/number_dataset_signal_region_data_mj +  
        #        number_dataset_signal_region_error2_pseudodata_mj/number_dataset_signal_region_pseudodata_mj/number_dataset_signal_region_pseudodata_mj +  
        #        number_dataset_signal_region_before_mva_error2_data_mj/number_dataset_signal_region_before_mva_data_mj/number_dataset_signal_region_data_mj +  
        #        number_dataset_signal_region_before_mva_error2_pseudodata_mj/number_dataset_signal_region_before_mva_pseudodata_mj/number_dataset_signal_region_before_mva_pseudodata_mj 
        #        );
        #
        #print "wtagger_eff_MC   = %s "%(wtagger_eff_MC )
        #print "wtagger_eff_data = %s "%(wtagger_eff_data )
        #print "wtagger_eff_reweight = %s +/- %s"%(wtagger_eff_reweight, wtagger_eff_reweight_err)
        #self.file_out_ttbar_control.write("wtagger_eff_MC   = %s \n"%(wtagger_eff_MC ));
        #self.file_out_ttbar_control.write("wtagger_eff_data = %s \n"%(wtagger_eff_data ));
        #self.file_out_ttbar_control.write("wtagger_eff_reweight = %s +/- %s\n"%(wtagger_eff_reweight, wtagger_eff_reweight_err));

        ## wtagger reweight: reweight the event number difference in signal region after mva cut between MC and data
        #wtagger_reweight=number_dataset_signal_region_data_mj/number_dataset_signal_region_pseudodata_mj;
        #wtagger_reweight_err=wtagger_reweight*TMath.Sqrt( 
        #        number_dataset_signal_region_error2_data_mj/number_dataset_signal_region_data_mj/number_dataset_signal_region_data_mj +  
        #        number_dataset_signal_region_error2_pseudodata_mj/number_dataset_signal_region_pseudodata_mj/number_dataset_signal_region_pseudodata_mj 
        #        );
        #print "wtagger_reweight = %s +/- %s"%(wtagger_reweight, wtagger_reweight_err)
        #self.file_out_ttbar_control.write("wtagger_reweight = %s +/- %s\n"%(wtagger_reweight, wtagger_reweight_err));

    ############# ---------------------------------------------------
    def ScaleFactor_forPureWJet_TTbar_controlsample(self,in_file_name, fit_or_not=1):#stateoftau2tau1cut="", or "failtau2tau1cut_"

        #dataset after tau2tau1 cut
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");
        rdataset_data_mj = self.workspace4fit_.data("rdataset_data_"+self.channel+"_mj"); 
        rdataset_TTbar_mj = self.workspace4fit_.data("rdataset_TTbar_"+self.channel+"_mj"); 
        rdataset_STop_mj = self.workspace4fit_.data("rdataset_STop_"+self.channel+"_mj"); 
        rdataset_VV_mj = self.workspace4fit_.data("rdataset_VV_"+self.channel+"_mj"); 
        rdataset_WJets_mj = self.workspace4fit_.data("rdataset_WJets0_"+self.channel+"_mj"); 

        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_TTbar_mj);
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_STop_mj)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_VV_mj)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_WJets_mj)
        model_histpdf_TTbar= self.workspace4fit_.pdf(rdataset_TTbar_mj.GetName()+"_histpdf")
        model_histpdf_STop = self.workspace4fit_.pdf(rdataset_STop_mj.GetName()+"_histpdf")
        model_histpdf_VV   = self.workspace4fit_.pdf(rdataset_VV_mj.GetName()+"_histpdf")
        model_histpdf_WJets   = self.workspace4fit_.pdf(rdataset_WJets_mj.GetName()+"_histpdf")
        number_TTbar=RooRealVar("rrv_number_TTbar"+"_"+self.channel ,"rrv_number_TTbar"+"_"+self.channel,rdataset_TTbar_mj.sumEntries());
        number_STop =RooRealVar("rrv_number_STop"+"_"+self.channel ,"rrv_number_STop"+"_"+self.channel,rdataset_STop_mj.sumEntries());
        number_VV   =RooRealVar("rrv_number_VV"+"_"+self.channel   ,"rrv_number_VV"+"_"+self.channel,rdataset_VV_mj.sumEntries());
        number_WJets=RooRealVar("rrv_number_WJets"+"_"+self.channel,"rrv_number_WJets"+"_"+self.channel,rdataset_WJets_mj.sumEntries());
        model_TTbar_STop_VV_WJets=RooAddPdf("model_TTbar_STop_VV_WJets"+"_"+self.channel,"model_TTbar_STop_VV_WJets"+"_"+self.channel, RooArgList(model_histpdf_TTbar, model_histpdf_STop, model_histpdf_VV, model_histpdf_WJets), RooArgList(number_TTbar, number_STop, number_VV, number_WJets) );
        getattr(self.workspace4fit_,"import")(model_TTbar_STop_VV_WJets);

        #dataset fail tau2tau1 cut
        rdataset_data_mj_fail = self.workspace4fit_.data("rdataset_data_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_TTbar_mj_fail = self.workspace4fit_.data("rdataset_TTbar_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_STop_mj_fail = self.workspace4fit_.data("rdataset_STop_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_VV_mj_fail = self.workspace4fit_.data("rdataset_VV_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_WJets_mj_fail = self.workspace4fit_.data("rdataset_WJets0_"+"failtau2tau1cut_"+self.channel+"_mj"); 

        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_TTbar_mj_fail);
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_STop_mj_fail)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_VV_mj_fail)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_WJets_mj_fail)
        model_histpdf_TTbar_fail= self.workspace4fit_.pdf(rdataset_TTbar_mj_fail.GetName()+"_histpdf")
        model_histpdf_STop_fail = self.workspace4fit_.pdf(rdataset_STop_mj_fail.GetName()+"_histpdf")
        model_histpdf_VV_fail   = self.workspace4fit_.pdf(rdataset_VV_mj_fail.GetName()+"_histpdf")
        model_histpdf_WJets_fail= self.workspace4fit_.pdf(rdataset_WJets_mj_fail.GetName()+"_histpdf")
        number_TTbar_fail =RooRealVar("rrv_number_TTbar_fail"+"_"+self.channel ,"rrv_number_TTbar_fail"+"_"+self.channel,rdataset_TTbar_mj_fail.sumEntries());
        number_STop_fail =RooRealVar("rrv_number_STop_fail"+"_"+self.channel ,"rrv_number_STop_fail"+"_"+self.channel,rdataset_STop_mj_fail.sumEntries());
        number_VV_fail   =RooRealVar("rrv_number_VV_fail"+"_"+self.channel   ,"rrv_number_VV_fail"+"_"+self.channel,rdataset_VV_mj_fail.sumEntries());
        number_WJets_fail=RooRealVar("rrv_number_WJets_fail"+"_"+self.channel,"rrv_number_WJets_fail"+"_"+self.channel,rdataset_WJets_mj_fail.sumEntries());
        model_TTbar_STop_VV_WJets_fail=RooAddPdf("model_TTbar_STop_VV_WJets_fail"+"_"+self.channel,"model_TTbar_STop_VV_WJets_fail"+"_"+self.channel, RooArgList(model_histpdf_TTbar_fail, model_histpdf_STop_fail, model_histpdf_VV_fail, model_histpdf_WJets_fail), RooArgList(number_TTbar_fail, number_STop_fail, number_VV_fail, number_WJets_fail) );
        getattr(self.workspace4fit_,"import")(model_TTbar_STop_VV_WJets_fail);

        scale_number_TTbar_STop_VV_WJets=(rdataset_TTbar_mj.sumEntries()+rdataset_STop_mj.sumEntries()+rdataset_VV_mj.sumEntries() +rdataset_WJets_mj.sumEntries() )/( rdataset_data_mj.sumEntries()+rdataset_data_mj_fail.sumEntries() ) 
        scale_number_TTbar_STop_VV_WJets_fail=(rdataset_TTbar_mj_fail.sumEntries()+rdataset_STop_mj_fail.sumEntries()+rdataset_VV_mj_fail.sumEntries() +rdataset_WJets_mj_fail.sumEntries() )/( rdataset_data_mj.sumEntries()+rdataset_data_mj_fail.sumEntries() ) 

        rrv_scale_number_TTbar_STop_VV_WJets=RooRealVar("rrv_scale_number_TTbar_STop_VV_WJets","rrv_scale_number_TTbar_STop_VV_WJets",scale_number_TTbar_STop_VV_WJets);
        rrv_scale_number_TTbar_STop_VV_WJets_fail=RooRealVar("rrv_scale_number_TTbar_STop_VV_WJets_fail","rrv_scale_number_TTbar_STop_VV_WJets_fail",scale_number_TTbar_STop_VV_WJets_fail);
        getattr(self.workspace4fit_,"import")(rrv_scale_number_TTbar_STop_VV_WJets);
        getattr(self.workspace4fit_,"import")(rrv_scale_number_TTbar_STop_VV_WJets_fail);

        model_STop=self.get_STop_mj_Model("_STop");
        model_VV=self.get_VV_mj_Model("_VV");
        model_WJets=self.get_General_mj_Model("_WJets0");

        model_STop_fail=self.get_STop_mj_Model("_STop_failtau2tau1cut");
        model_VV_fail=self.get_VV_mj_Model("_VV_failtau2tau1cut");
        model_WJets_fail=self.get_General_mj_Model("_WJets0_failtau2tau1cut");
        #fit data
        self.constrainslist_data=[];
        model_bkg_data = self.make_Model("_bkg_data","ErfExp_ttbar","_mj",self.constrainslist_data);
        model_bkg_data_fail = self.make_Model("_bkg_data_failtau2tau1cut","ErfExp_ttbar_failtau2tau1cut","_mj",self.constrainslist_data);
        #model_ttbar_data = self.make_Model("_ttbar_data","2Gaus_ttbar","_mj",self.constrainslist_data);
        #model_ttbar_data_fail = self.make_Model("_ttbar_data_failtau2tau1cut","GausChebychev_ttbar_failtau2tau1cut","_mj",self.constrainslist_data);
        model_ttbar_data = self.make_Model_for_ttbar_controlsample("_ttbar_data","2Gaus_ttbar","_mj",self.constrainslist_data);
        model_ttbar_data_fail = self.make_Model_for_ttbar_controlsample("_ttbar_data_failtau2tau1cut","GausChebychev_ttbar_failtau2tau1cut","_mj",self.constrainslist_data);
        model_data_fail=RooAddPdf("model_data_failtau2tau1cut_"+self.channel,"model_data_failtau2tau1cut_"+self.channel, RooArgList(model_ttbar_data_fail, model_bkg_data_fail, model_STop_fail, model_VV_fail, model_WJets_fail));
        model_data=RooAddPdf("model_data_"+self.channel,"model_data_"+self.channel, RooArgList(model_ttbar_data, model_bkg_data, model_STop, model_VV, model_WJets));
        getattr(self.workspace4fit_,"import")(model_data);
        getattr(self.workspace4fit_,"import")(model_data_fail);


        category_p_f=self.workspace4fit_.cat("category_p_f_"+self.channel);
        #category_p_f=RooCategory("category_p_f_"+self.channel,"category_p_f_"+self.channel);
        #category_p_f.defineType("pass",1); category_p_f.defineType("fail",2);

        simPdf_data=RooSimultaneous("simPdf_data_"+self.channel,"simPdf_data_"+self.channel,category_p_f);
        simPdf_data.addPdf(model_data,"pass");
        simPdf_data.addPdf(model_data_fail,"fail");
        combData_p_f_data=self.workspace4fit_.data("combData_p_f_data_"+self.channel);#_data_failtau2tau1cut
        simPdf_data.Print();
        combData_p_f_data.Print();

        pdfconstrainslist_data=RooArgSet("pdfconstrainslist_data_"+self.channel);
        for i in range(len(self.constrainslist_data)):
            self.workspace4fit_.pdf(self.constrainslist_data[i]).Print();
            pdfconstrainslist_data.add(self.workspace4fit_.pdf(self.constrainslist_data[i]) );
        if fit_or_not :
            rfresult_data=simPdf_data.fitTo(combData_p_f_data,RooFit.Save(kTRUE), RooFit.Range("controlsample_fitting_range"),RooFit.ExternalConstraints(pdfconstrainslist_data));
            rfresult_data=simPdf_data.fitTo(combData_p_f_data,RooFit.Save(kTRUE), RooFit.Range("controlsample_fitting_range"),RooFit.ExternalConstraints(pdfconstrainslist_data));
            rfresult_data.Print();
        #fit TotalMC
        self.constrainslist_TotalMC=[];
        model_bkg_TotalMC = self.make_Model("_bkg_TotalMC","ErfExp_ttbar","_mj",self.constrainslist_TotalMC);
        model_bkg_TotalMC_fail = self.make_Model("_bkg_TotalMC_failtau2tau1cut","ErfExp_ttbar_failtau2tau1cut","_mj",self.constrainslist_TotalMC);
        #model_ttbar_TotalMC = self.make_Model("_ttbar_TotalMC","2Gaus_ttbar","_mj",self.constrainslist_TotalMC);
        #model_ttbar_TotalMC_fail = self.make_Model("_ttbar_TotalMC_failtau2tau1cut","GausChebychev_ttbar_failtau2tau1cut","_mj",self.constrainslist_TotalMC);
        model_ttbar_TotalMC = self.make_Model_for_ttbar_controlsample("_ttbar_TotalMC","2Gaus_ttbar","_mj",self.constrainslist_TotalMC);
        model_ttbar_TotalMC_fail = self.make_Model_for_ttbar_controlsample("_ttbar_TotalMC_failtau2tau1cut","GausChebychev_ttbar_failtau2tau1cut","_mj",self.constrainslist_TotalMC);
        model_TotalMC_fail=RooAddPdf("model_TotalMC_failtau2tau1cut_"+self.channel,"model_TotalMC_failtau2tau1cut_"+self.channel, RooArgList(model_ttbar_TotalMC_fail, model_bkg_TotalMC_fail, model_STop_fail, model_VV_fail, model_WJets_fail));
        model_TotalMC=RooAddPdf("model_TotalMC_"+self.channel,"model_TotalMC_"+self.channel, RooArgList(model_ttbar_TotalMC, model_bkg_TotalMC, model_STop, model_VV, model_WJets));
        getattr(self.workspace4fit_,"import")(model_TotalMC_fail);
        getattr(self.workspace4fit_,"import")(model_TotalMC);

        simPdf_TotalMC=RooSimultaneous("simPdf_TotalMC_"+self.channel,"simPdf_TotalMC_"+self.channel,category_p_f);
        simPdf_TotalMC.addPdf(model_TotalMC,"pass");
        simPdf_TotalMC.addPdf(model_TotalMC_fail,"fail");
        combData_p_f_TotalMC=self.workspace4fit_.data("combData_p_f_TotalMC_"+self.channel);

        pdfconstrainslist_TotalMC=RooArgSet("pdfconstrainslist_TotalMC_"+self.channel);
        for i in range(len(self.constrainslist_TotalMC)):
            self.workspace4fit_.pdf(self.constrainslist_TotalMC[i]).Print();
            pdfconstrainslist_TotalMC.add(self.workspace4fit_.pdf(self.constrainslist_TotalMC[i]) );
        if fit_or_not :
            rfresult_TotalMC=simPdf_TotalMC.fitTo(combData_p_f_TotalMC,RooFit.Save(kTRUE), RooFit.Range("controlsample_fitting_range"),RooFit.ExternalConstraints(pdfconstrainslist_TotalMC));
            rfresult_TotalMC=simPdf_TotalMC.fitTo(combData_p_f_TotalMC,RooFit.Save(kTRUE), RooFit.Range("controlsample_fitting_range"),RooFit.ExternalConstraints(pdfconstrainslist_TotalMC));
            rfresult_TotalMC.Print();

        xframe_data=rrv_mass_j.frame();
        xframe_data_fail=rrv_mass_j.frame();

        combData_p_f_data.plotOn(xframe_data,RooFit.Name("data invisi"), RooFit.Cut("category_p_f_%s==category_p_f_%s::pass"%(self.channel,self.channel)));
        combData_p_f_data.plotOn(xframe_data_fail,RooFit.Name("data invisi"), RooFit.Cut("category_p_f_%s==category_p_f_%s::fail"%(self.channel,self.channel)));
        
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("TTbar"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("STop"),RooFit.Components("%s,%s,%s"%(model_histpdf_STop.GetName(), model_histpdf_VV.GetName(), model_histpdf_WJets.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("VV"),RooFit.Components("%s,%s"%(model_histpdf_VV.GetName(), model_histpdf_WJets.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("WJets"),RooFit.Components("%s"%(model_histpdf_WJets.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines())

        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("TTbar"), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("STop"),RooFit.Components("%s,%s,%s"%(model_histpdf_STop_fail.GetName(), model_histpdf_VV_fail.GetName(), model_histpdf_WJets_fail.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("VV"),RooFit.Components("%s,%s"%(model_histpdf_VV_fail.GetName(), model_histpdf_WJets_fail.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("WJets"),RooFit.Components("%s"%( model_histpdf_WJets_fail.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines())


        combData_p_f_data.plotOn(xframe_data,RooFit.Name("data"), RooFit.Cut("category_p_f_%s==category_p_f_%s::pass"%(self.channel,self.channel)));
        combData_p_f_data.plotOn(xframe_data_fail,RooFit.Name("data"), RooFit.Cut("category_p_f_%s==category_p_f_%s::fail"%(self.channel,self.channel)));

        if self.wtagger_cut<10:
            simPdf_TotalMC.plotOn(xframe_data,RooFit.Name("MC fit"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.LineStyle(kDashed))
            #simPdf_TotalMC.plotOn(xframe_data,RooFit.Name("MC fit comp"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("model_bkg_TotalMC_%s_mj"%(self.channel)), RooFit.LineColor(kRed), RooFit.LineStyle(kDashed))
            simPdf_TotalMC.plotOn(xframe_data,RooFit.Name("MC fit comp"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%(model_bkg_TotalMC.GetName(),model_STop.GetName(),model_VV.GetName(),model_WJets.GetName()) ), RooFit.LineColor(kRed), RooFit.LineStyle(kDashed))

            simPdf_data.plotOn(xframe_data,RooFit.Name("data fit"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))
            #simPdf_data.plotOn(xframe_data,RooFit.Name("data fit comp"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("model_bkg_data_%s_mj"%(self.channel)), RooFit.LineColor(kRed))
            simPdf_data.plotOn(xframe_data,RooFit.Name("data fit comp"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%(model_bkg_data.GetName(),model_STop.GetName(),model_VV.GetName(),model_WJets.GetName())), RooFit.LineColor(kRed))
            simPdf_data.plotOn(xframe_data,RooFit.Name("data fit invisi"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))


            simPdf_TotalMC.plotOn(xframe_data_fail,RooFit.Name("MC fit"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.LineStyle(kDashed))
            #simPdf_TotalMC.plotOn(xframe_data_fail,RooFit.Name("MC fit comp"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("model_bkg_TotalMC_failtau2tau1cut_%s_mj"%(self.channel)), RooFit.LineColor(kRed), RooFit.LineStyle(kDashed))
            simPdf_TotalMC.plotOn(xframe_data_fail,RooFit.Name("MC fit comp"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%(model_bkg_TotalMC_fail.GetName(),model_STop_fail.GetName(),model_VV_fail.GetName(),model_WJets_fail.GetName())), RooFit.LineColor(kRed), RooFit.LineStyle(kDashed))
            simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))
            #simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit comp"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("model_bkg_data_failtau2tau1cut_%s_mj"%(self.channel)), RooFit.LineColor(kRed))
            simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit comp"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%(model_bkg_data_fail.GetName(),model_STop_fail.GetName(),model_VV_fail.GetName(),model_WJets_fail.GetName())), RooFit.LineColor(kRed))
            simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit invisi"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))
        leg_data=self.legend4Plot(xframe_data,0)
        xframe_data.addObject(leg_data)
        leg_data_fail=self.legend4Plot(xframe_data_fail,0)
        xframe_data_fail.addObject(leg_data_fail)

        #add mean and width
        rrv_mean_gaus_data    =self.workspace4fit_.var("rrv_mean1_gaus_ttbar_data"+"_"+self.channel);
        rrv_sigma_gaus_data   =self.workspace4fit_.var("rrv_sigma1_gaus_ttbar_data"+"_"+self.channel);
        rrv_mean_gaus_TotalMC =self.workspace4fit_.var("rrv_mean1_gaus_ttbar_TotalMC"+"_"+self.channel);
        rrv_sigma_gaus_TotalMC=self.workspace4fit_.var("rrv_sigma1_gaus_ttbar_TotalMC"+"_"+self.channel);
        if rrv_mean_gaus_TotalMC: 
            tl_MC_mean   =TLatex(0.25 ,0.62, ("Mean_{MC  } = %3.1f #pm %2.1f")%(rrv_mean_gaus_TotalMC.getVal(), rrv_mean_gaus_TotalMC.getError()) );
            tl_MC_sigma  =TLatex(0.25 ,0.57, ("Sigma_{MC  }= %2.1f #pm %2.1f")%(rrv_sigma_gaus_TotalMC.getVal(), rrv_sigma_gaus_TotalMC.getError()) );
            tl_MC_mean.SetNDC(); tl_MC_sigma.SetNDC();
            tl_MC_mean.SetTextSize(0.03)
            tl_MC_sigma.SetTextSize(0.03)
            if self.wtagger_cut<10:
                xframe_data.addObject(tl_MC_mean);
                xframe_data.addObject(tl_MC_sigma);
        if rrv_mean_gaus_data: 
            tl_data_mean =TLatex(0.25 ,0.52, ("Mean_{data} = %3.1f #pm %2.1f")%(rrv_mean_gaus_data.getVal(), rrv_mean_gaus_data.getError()) );
            tl_data_sigma=TLatex(0.25 ,0.47, ("Sigma_{data}= %2.1f #pm %2.1f")%(rrv_sigma_gaus_data.getVal(), rrv_sigma_gaus_data.getError()) );
            tl_data_mean.SetNDC(); tl_data_sigma.SetNDC();
            tl_data_mean.SetTextSize(0.03)
            tl_data_sigma.SetTextSize(0.03)
            if self.wtagger_cut<10:
                xframe_data.addObject(tl_data_mean);
                xframe_data.addObject(tl_data_sigma);
        #signal window
        lowerLine = TLine(self.mj_signal_min,0.,self.mj_signal_min,xframe_data.GetMaximum()); lowerLine.SetLineWidth(2); lowerLine.SetLineColor(kGray+2); lowerLine.SetLineStyle(9);
        upperLine = TLine(self.mj_signal_max,0.,self.mj_signal_max,xframe_data.GetMaximum()); upperLine.SetLineWidth(2); upperLine.SetLineColor(kGray+2); upperLine.SetLineStyle(9);
        xframe_data.addObject(lowerLine); xframe_data.addObject(upperLine);
        lowerLine = TLine(self.mj_signal_min,0.,self.mj_signal_min,xframe_data_fail.GetMaximum()); lowerLine.SetLineWidth(2); lowerLine.SetLineColor(kGray+2); lowerLine.SetLineStyle(9);
        upperLine = TLine(self.mj_signal_max,0.,self.mj_signal_max,xframe_data_fail.GetMaximum()); upperLine.SetLineWidth(2); upperLine.SetLineColor(kGray+2); upperLine.SetLineStyle(9);
        xframe_data_fail.addObject(lowerLine); xframe_data_fail.addObject(upperLine);
        ##pull
        #hpull=xframe_data.pullHist();
        #mplot_pull = rrv_mass_j.frame(RooFit.Title("Pull Distribution"));
        #mplot_pull.addPlotable(hpull,"P");
        #mplot_pull.SetTitle("PULL");
        #mplot_pull.GetYaxis().SetRangeUser(-5,5);
         
        xframe_data.GetYaxis().SetRangeUser(1e-2,xframe_data.GetMaximum()*1.1);
        xframe_data_fail.GetYaxis().SetRangeUser(1e-2,xframe_data_fail.GetMaximum()*1.1);


        self.draw_canvas1(xframe_data,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max),"control_%s_%s"%(self.wtagger_label,self.channel));
        self.draw_canvas1(xframe_data_fail,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max),"control_%s_%s_fail"%(self.wtagger_label,self.channel));


        self.ShowParam_Pdf(simPdf_data,RooArgSet(rrv_mass_j,category_p_f));
        self.ShowParam_Pdf(simPdf_TotalMC,RooArgSet(rrv_mass_j,category_p_f));
        if fit_or_not:
            rfresult_TotalMC.covarianceMatrix().Print();
            rfresult_data.covarianceMatrix().Print();
            rfresult_TotalMC.Print();
            rfresult_data.Print();

 
    ############# ---------------------------------------------------
    def draw_ScaleFactor_forPureWJet_TTbar_controlsample(self,in_file_name, fit_or_not=1):#stateoftau2tau1cut="", or "failtau2tau1cut_"

        #dataset after tau2tau1 cut
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");
        rdataset_data_mj = self.workspace4fit_.data("rdataset_data_"+self.channel+"_mj"); 
        rdataset_TTbar_mj = self.workspace4fit_.data("rdataset_TTbar_"+self.channel+"_mj"); 
        rdataset_STop_mj = self.workspace4fit_.data("rdataset_STop_"+self.channel+"_mj"); 
        rdataset_VV_mj = self.workspace4fit_.data("rdataset_VV_"+self.channel+"_mj"); 
        rdataset_WJets_mj = self.workspace4fit_.data("rdataset_WJets0_"+self.channel+"_mj"); 

        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_TTbar_mj);
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_STop_mj)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_VV_mj)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_WJets_mj)
        model_histpdf_TTbar= self.workspace4fit_.pdf(rdataset_TTbar_mj.GetName()+"_histpdf")
        model_histpdf_STop = self.workspace4fit_.pdf(rdataset_STop_mj.GetName()+"_histpdf")
        model_histpdf_VV   = self.workspace4fit_.pdf(rdataset_VV_mj.GetName()+"_histpdf")
        model_histpdf_WJets   = self.workspace4fit_.pdf(rdataset_WJets_mj.GetName()+"_histpdf")
        number_TTbar=RooRealVar("rrv_number_TTbar"+"_"+self.channel ,"rrv_number_TTbar"+"_"+self.channel,rdataset_TTbar_mj.sumEntries());
        number_STop =RooRealVar("rrv_number_STop"+"_"+self.channel ,"rrv_number_STop"+"_"+self.channel,rdataset_STop_mj.sumEntries());
        number_VV   =RooRealVar("rrv_number_VV"+"_"+self.channel   ,"rrv_number_VV"+"_"+self.channel,rdataset_VV_mj.sumEntries());
        number_WJets=RooRealVar("rrv_number_WJets"+"_"+self.channel,"rrv_number_WJets"+"_"+self.channel,rdataset_WJets_mj.sumEntries());
        model_TTbar_STop_VV_WJets=self.workspace4fit_.pdf(    "model_TTbar_STop_VV_WJets"+"_"+self.channel);

        #dataset fail tau2tau1 cut
        rdataset_data_mj_fail = self.workspace4fit_.data("rdataset_data_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_TTbar_mj_fail = self.workspace4fit_.data("rdataset_TTbar_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_STop_mj_fail = self.workspace4fit_.data("rdataset_STop_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_VV_mj_fail = self.workspace4fit_.data("rdataset_VV_"+"failtau2tau1cut_"+self.channel+"_mj"); 
        rdataset_WJets_mj_fail = self.workspace4fit_.data("rdataset_WJets0_"+"failtau2tau1cut_"+self.channel+"_mj"); 

        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_TTbar_mj_fail);
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_STop_mj_fail)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_VV_mj_fail)
        self.change_dataset_to_histpdf(rrv_mass_j, rdataset_WJets_mj_fail)
        model_histpdf_TTbar_fail= self.workspace4fit_.pdf(rdataset_TTbar_mj_fail.GetName()+"_histpdf")
        model_histpdf_STop_fail = self.workspace4fit_.pdf(rdataset_STop_mj_fail.GetName()+"_histpdf")
        model_histpdf_VV_fail   = self.workspace4fit_.pdf(rdataset_VV_mj_fail.GetName()+"_histpdf")
        model_histpdf_WJets_fail= self.workspace4fit_.pdf(rdataset_WJets_mj_fail.GetName()+"_histpdf")
        number_TTbar_fail =RooRealVar("rrv_number_TTbar_fail"+"_"+self.channel ,"rrv_number_TTbar_fail"+"_"+self.channel,rdataset_TTbar_mj_fail.sumEntries());
        number_STop_fail =RooRealVar("rrv_number_STop_fail"+"_"+self.channel ,"rrv_number_STop_fail"+"_"+self.channel,rdataset_STop_mj_fail.sumEntries());
        number_VV_fail   =RooRealVar("rrv_number_VV_fail"+"_"+self.channel   ,"rrv_number_VV_fail"+"_"+self.channel,rdataset_VV_mj_fail.sumEntries());
        number_WJets_fail=RooRealVar("rrv_number_WJets_fail"+"_"+self.channel,"rrv_number_WJets_fail"+"_"+self.channel,rdataset_WJets_mj_fail.sumEntries());
        model_TTbar_STop_VV_WJets_fail=self.workspace4fit_.pdf("model_TTbar_STop_VV_WJets_fail"+"_"+self.channel);

        scale_number_TTbar_STop_VV_WJets=(rdataset_TTbar_mj.sumEntries()+rdataset_STop_mj.sumEntries()+rdataset_VV_mj.sumEntries() +rdataset_WJets_mj.sumEntries() )/( rdataset_data_mj.sumEntries()+rdataset_data_mj_fail.sumEntries() ) 
        scale_number_TTbar_STop_VV_WJets_fail=(rdataset_TTbar_mj_fail.sumEntries()+rdataset_STop_mj_fail.sumEntries()+rdataset_VV_mj_fail.sumEntries() +rdataset_WJets_mj_fail.sumEntries() )/( rdataset_data_mj.sumEntries()+rdataset_data_mj_fail.sumEntries() ) 


        model_STop=self.get_STop_mj_Model("_STop");
        model_VV=self.get_VV_mj_Model("_VV");
        model_WJets=self.get_General_mj_Model("_WJets0");

        model_STop_fail=self.get_STop_mj_Model("_STop_failtau2tau1cut");
        model_VV_fail=self.get_VV_mj_Model("_VV_failtau2tau1cut");
        model_WJets_fail=self.get_General_mj_Model("_WJets0_failtau2tau1cut");

        model_data_fail=self.workspace4fit_.pdf("model_data_failtau2tau1cut_"+self.channel)
        model_data=self.workspace4fit_.pdf("model_data_"+self.channel);

        category_p_f=self.workspace4fit_.cat("category_p_f_"+self.channel);

        simPdf_data=RooSimultaneous("simPdf_data_"+self.channel,"simPdf_data_"+self.channel,category_p_f);
        simPdf_data.addPdf(model_data,"pass");
        simPdf_data.addPdf(model_data_fail,"fail");
        combData_p_f_data=self.workspace4fit_.data("combData_p_f_data_"+self.channel);#_data_failtau2tau1cut
        simPdf_data.Print();
        combData_p_f_data.Print();

        model_TotalMC_fail=self.workspace4fit_.pdf("model_TotalMC_failtau2tau1cut_"+self.channel);
        model_TotalMC=self.workspace4fit_.pdf("model_TotalMC_"+self.channel);

        simPdf_TotalMC=RooSimultaneous("simPdf_TotalMC_"+self.channel,"simPdf_TotalMC_"+self.channel,category_p_f);
        simPdf_TotalMC.addPdf(model_TotalMC,"pass");
        simPdf_TotalMC.addPdf(model_TotalMC_fail,"fail");
        combData_p_f_TotalMC=self.workspace4fit_.data("combData_p_f_TotalMC_"+self.channel);


        xframe_data=rrv_mass_j.frame();
        xframe_data_fail=rrv_mass_j.frame();

        combData_p_f_data.plotOn(xframe_data,RooFit.Name("data invisi"), RooFit.Cut("category_p_f_%s==category_p_f_%s::pass"%(self.channel, self.channel)));
        combData_p_f_data.plotOn(xframe_data_fail,RooFit.Name("data invisi"), RooFit.Cut("category_p_f_%s==category_p_f_%s::fail"%(self.channel, self.channel)));
        
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("TTbar"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("STop"),RooFit.Components("%s,%s,%s"%(model_histpdf_STop.GetName(), model_histpdf_VV.GetName(), model_histpdf_WJets.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("VV"),RooFit.Components("%s,%s"%(model_histpdf_VV.GetName(), model_histpdf_WJets.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets.plotOn(xframe_data,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets),RooFit.Name("WJets"),RooFit.Components("%s"%(model_histpdf_WJets.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines())

        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("TTbar"), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("STop"),RooFit.Components("%s,%s,%s"%(model_histpdf_STop_fail.GetName(), model_histpdf_VV_fail.GetName(), model_histpdf_WJets_fail.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("VV"),RooFit.Components("%s,%s"%(model_histpdf_VV_fail.GetName(), model_histpdf_WJets_fail.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines())
        model_TTbar_STop_VV_WJets_fail.plotOn(xframe_data_fail,RooFit.Normalization(scale_number_TTbar_STop_VV_WJets_fail),RooFit.Name("WJets"),RooFit.Components("%s"%( model_histpdf_WJets_fail.GetName()) ), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines())


        combData_p_f_data.plotOn(xframe_data,RooFit.Name("data"), RooFit.Cut("category_p_f_%s==category_p_f_%s::pass"%(self.channel,self.channel)));
        combData_p_f_data.plotOn(xframe_data_fail,RooFit.Name("data"), RooFit.Cut("category_p_f_%s==category_p_f_%s::fail"%(self.channel,self.channel)));

        #combData_p_f_TotalMC.plotOn(xframe_data,RooFit.Name("TotalMC"), RooFit.Cut("category_p_f==category_p_f::pass"), RooFit.MarkerColor(kRed));
        #combData_p_f_TotalMC.plotOn(xframe_data_fail,RooFit.Name("TotalMC"), RooFit.Cut("category_p_f==category_p_f::fail"), RooFit.MarkerColor(kRed));
        if self.wtagger_cut<10:
            simPdf_TotalMC.plotOn(xframe_data,RooFit.Name("MC fit"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.LineStyle(kDashed))
            simPdf_TotalMC.plotOn(xframe_data,RooFit.Name("MC fit comp"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC), RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%("model_bkg_TotalMC_%s_mj"%(self.channel),"model_STop_%s_mj"%(self.channel),"model_VV_%s_mj"%(self.channel),"model_WJets0_%s_mj"%(self.channel)) ), RooFit.LineColor(kRed), RooFit.LineStyle(kDashed))

            simPdf_data.plotOn(xframe_data,RooFit.Name("data fit"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))
            simPdf_data.plotOn(xframe_data,RooFit.Name("data fit comp"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%("model_bkg_data_%s_mj"%(self.channel),"model_STop_%s_mj"%(self.channel),"model_VV_%s_mj"%(self.channel),"model_WJets0_%s_mj"%(self.channel))), RooFit.LineColor(kRed))
            simPdf_data.plotOn(xframe_data,RooFit.Name("data fit invisi"),RooFit.Slice(category_p_f,"pass"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))


            simPdf_TotalMC.plotOn(xframe_data_fail,RooFit.Name("MC fit"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.LineStyle(kDashed))
            simPdf_TotalMC.plotOn(xframe_data_fail,RooFit.Name("MC fit comp"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_TotalMC),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%("model_bkg_TotalMC_failtau2tau1cut_%s_mj"%(self.channel),"model_STop_failtau2tau1cut_%s_mj"%(self.channel),"model_VV_failtau2tau1cut_%s_mj"%(self.channel),"model_WJets0_failtau2tau1cut_%s_mj"%(self.channel))), RooFit.LineColor(kRed), RooFit.LineStyle(kDashed))

            simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))
            simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit comp"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"), RooFit.Components("%s,%s,%s,%s"%("model_bkg_data_failtau2tau1cut_%s_mj"%(self.channel),"model_STop_failtau2tau1cut_%s_mj"%(self.channel),"model_VV_failtau2tau1cut_%s_mj"%(self.channel),"model_WJets0_failtau2tau1cut_%s_mj"%(self.channel))), RooFit.LineColor(kRed))
            simPdf_data.plotOn(xframe_data_fail,RooFit.Name("data fit invisi"),RooFit.Slice(category_p_f,"fail"),RooFit.ProjWData(RooArgSet(category_p_f),combData_p_f_data),RooFit.NormRange("controlsample_fitting_range"))
        leg_data=self.legend4Plot(xframe_data,0)
        xframe_data.addObject(leg_data)
        leg_data_fail=self.legend4Plot(xframe_data_fail,0)
        xframe_data_fail.addObject(leg_data_fail)

        #add mean and width
        tmp_channel="el";
        if self.workspace4fit_.var("rrv_mean1_gaus_ttbar_data_el"): tmp_channel="el";
        else: tmp_channel="mu";

        rrv_mean_gaus_data    =self.workspace4fit_.var("rrv_mean1_gaus_ttbar_data"+"_"+tmp_channel);
        rrv_sigma_gaus_data   =self.workspace4fit_.var("rrv_sigma1_gaus_ttbar_data"+"_"+tmp_channel);
        rrv_mean_gaus_TotalMC =self.workspace4fit_.var("rrv_mean1_gaus_ttbar_TotalMC"+"_"+tmp_channel);
        rrv_sigma_gaus_TotalMC=self.workspace4fit_.var("rrv_sigma1_gaus_ttbar_TotalMC"+"_"+tmp_channel);
        if rrv_mean_gaus_TotalMC: 
            tl_MC_mean   =TLatex(0.25 ,0.62, ("Mean_{MC  } = %3.1f #pm %2.1f")%(rrv_mean_gaus_TotalMC.getVal(), rrv_mean_gaus_TotalMC.getError()) );
            tl_MC_sigma  =TLatex(0.25 ,0.57, ("Sigma_{MC  }= %2.1f #pm %2.1f")%(rrv_sigma_gaus_TotalMC.getVal(), rrv_sigma_gaus_TotalMC.getError()) );
            tl_MC_mean.SetNDC(); tl_MC_sigma.SetNDC();
            tl_MC_mean.SetTextSize(0.03)
            tl_MC_sigma.SetTextSize(0.03)
            if self.wtagger_cut<10:
                xframe_data.addObject(tl_MC_mean);
                xframe_data.addObject(tl_MC_sigma);

        if rrv_mean_gaus_data: 
            tl_data_mean =TLatex(0.25 ,0.52, ("Mean_{data} = %3.1f #pm %2.1f")%(rrv_mean_gaus_data.getVal(), rrv_mean_gaus_data.getError()) );
            tl_data_sigma=TLatex(0.25 ,0.47, ("Sigma_{data}= %2.1f #pm %2.1f")%(rrv_sigma_gaus_data.getVal(), rrv_sigma_gaus_data.getError()) );
            tl_data_mean.SetNDC(); tl_data_sigma.SetNDC();
            tl_data_mean.SetTextSize(0.03)
            tl_data_sigma.SetTextSize(0.03)
            if self.wtagger_cut<10:
                xframe_data.addObject(tl_data_mean);
                xframe_data.addObject(tl_data_sigma);
        #signal window
        lowerLine = TLine(self.mj_signal_min,0.,self.mj_signal_min,xframe_data.GetMaximum()); lowerLine.SetLineWidth(2); lowerLine.SetLineColor(kGray+2); lowerLine.SetLineStyle(9);
        upperLine = TLine(self.mj_signal_max,0.,self.mj_signal_max,xframe_data.GetMaximum()); upperLine.SetLineWidth(2); upperLine.SetLineColor(kGray+2); upperLine.SetLineStyle(9);
        xframe_data.addObject(lowerLine); xframe_data.addObject(upperLine);
        lowerLine = TLine(self.mj_signal_min,0.,self.mj_signal_min,xframe_data_fail.GetMaximum()); lowerLine.SetLineWidth(2); lowerLine.SetLineColor(kGray+2); lowerLine.SetLineStyle(9);
        upperLine = TLine(self.mj_signal_max,0.,self.mj_signal_max,xframe_data_fail.GetMaximum()); upperLine.SetLineWidth(2); upperLine.SetLineColor(kGray+2); upperLine.SetLineStyle(9);
        xframe_data_fail.addObject(lowerLine); xframe_data_fail.addObject(upperLine);
        ##pull
        #hpull=xframe_data.pullHist();
        #mplot_pull = rrv_mass_j.frame(RooFit.Title("Pull Distribution"));
        #mplot_pull.addPlotable(hpull,"P");
        #mplot_pull.SetTitle("PULL");
        #mplot_pull.GetYaxis().SetRangeUser(-5,5);
         
        xframe_data.GetYaxis().SetRangeUser(1e-2,xframe_data.GetMaximum()*1.1);
        xframe_data_fail.GetYaxis().SetRangeUser(1e-2,xframe_data_fail.GetMaximum()*1.1);
        self.draw_canvas1(xframe_data,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max),"control_%s_%s"%(self.wtagger_label,self.channel));
        self.draw_canvas1(xframe_data_fail,"plots_%s_%s/m_j_fitting_TTbar_controlsample_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max),"control_%s_%s_fail"%(self.wtagger_label,self.channel));


        ##calculate tau2tau1 cut eff(40-130) SF
        #eff_ttbar_data=self.workspace4fit_.var("eff_ttbar_data_"+self.channel);
        #eff_ttbar_TotalMC=self.workspace4fit_.var("eff_ttbar_TotalMC_"+self.channel);

        #SF_data2MC=eff_ttbar_data.getVal()/eff_ttbar_TotalMC.getVal();
        #SF_data2MC_err= SF_data2MC* TMath.Sqrt(
        #        (eff_ttbar_data.getError()/eff_ttbar_data.getVal())**2+
        #        (eff_ttbar_TotalMC.getError()/eff_ttbar_TotalMC.getVal())**2
        #        ) ;
        #print "data eff=%s +/- %s"%(eff_ttbar_data.getVal(),eff_ttbar_data.getError() );
        #print "MC   eff=%s +/- %s"%(eff_ttbar_TotalMC.getVal(),eff_ttbar_TotalMC.getError() );
        #print "%0.2f +/- %0.f%%"%(SF_data2MC,SF_data2MC_err/SF_data2MC*100 );


        ##calculate tau2tau1 cut  eff
        #self.eventnumber_in_signalregion("_data", model_ttbar_data, rfresult_data);
        #self.eventnumber_in_signalregion("_data_failtau2tau1cut", model_ttbar_data_fail, rfresult_data);
        #self.eventnumber_in_signalregion("_TotalMC", model_ttbar_TotalMC, rfresult_TotalMC);
        #self.eventnumber_in_signalregion("_TotalMC_failtau2tau1cut", model_ttbar_TotalMC_fail, rfresult_TotalMC);

        #rrv_number_data=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_data"+"_"+self.channel)
        #rrv_number_data_fail=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_data_failtau2tau1cut"+"_"+self.channel)
        #rrv_number_TotalMC=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_TotalMC"+"_"+self.channel)
        #rrv_number_TotalMC_fail=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_TotalMC_failtau2tau1cut"+"_"+self.channel)

        #rrv_number_data.Print();
        #rrv_number_data_fail.Print();
        #rrv_number_TotalMC.Print();
        #rrv_number_TotalMC_fail.Print();

        #SF_data2MC=(rrv_number_data.getVal()/rrv_number_data_fail.getVal()) / (rrv_number_TotalMC.getVal()/rrv_number_TotalMC_fail.getVal());
        #SF_data2MC_err= SF_data2MC* TMath.Sqrt(
        #        (rrv_number_data.getError()/rrv_number_data.getVal())**2+
        #        (rrv_number_data_fail.getError()/rrv_number_data_fail.getVal())**2+
        #        (rrv_number_TotalMC.getError()/rrv_number_TotalMC.getVal())**2+
        #        (rrv_number_TotalMC_fail.getError()/rrv_number_TotalMC_fail.getVal())**2 
        #        ) ;
        #print "data eff=%s"%(rrv_number_data.getVal()/rrv_number_data_fail.getVal() );
        #print "MC   eff=%s"%(rrv_number_TotalMC.getVal()/rrv_number_TotalMC_fail.getVal() );
        #print "%0.2f +/- %0.f%%"%(SF_data2MC,SF_data2MC_err/SF_data2MC*100 );

        ##calculate tau2tau1 cut  eff
        #self.eventnumber_in_signalregion("_data", model_ttbar_data, rfresult_data);
        #self.eventnumber_in_signalregion("_data_failtau2tau1cut", model_ttbar_data_fail, rfresult_data);
        #self.eventnumber_in_signalregion("_TotalMC", model_ttbar_TotalMC, rfresult_TotalMC);
        #self.eventnumber_in_signalregion("_TotalMC_failtau2tau1cut", model_ttbar_TotalMC_fail, rfresult_TotalMC);

        #rrv_number_data=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_data"+"_"+self.channel)
        #rrv_number_data_fail=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_data_failtau2tau1cut"+"_"+self.channel)
        #rrv_number_TotalMC=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_TotalMC"+"_"+self.channel)
        #rrv_number_TotalMC_fail=self.workspace4fit_.var("rrv_number_ttbar_in_mj_signal_region_from_fitting"+"_TotalMC_failtau2tau1cut"+"_"+self.channel)

        #rrv_number_data.Print();
        #rrv_number_data_fail.Print();
        #rrv_number_TotalMC.Print();
        #rrv_number_TotalMC_fail.Print();

        #SF_data2MC=(rrv_number_data.getVal()/rrv_number_data_fail.getVal()) / (rrv_number_TotalMC.getVal()/rrv_number_TotalMC_fail.getVal());
        #SF_data2MC_err= SF_data2MC* TMath.Sqrt(
        #        (rrv_number_data.getError()/rrv_number_data.getVal())**2+
        #        (rrv_number_data_fail.getError()/rrv_number_data_fail.getVal())**2+
        #        (rrv_number_TotalMC.getError()/rrv_number_TotalMC.getVal())**2+
        #        (rrv_number_TotalMC_fail.getError()/rrv_number_TotalMC_fail.getVal())**2 
        #        ) ;
        #print "data eff=%s"%(rrv_number_data.getVal()/rrv_number_data_fail.getVal() );
        #print "MC   eff=%s"%(rrv_number_TotalMC.getVal()/rrv_number_TotalMC_fail.getVal() );
        #print "%0.2f +/- %0.f%%"%(SF_data2MC,SF_data2MC_err/SF_data2MC*100 );

        #lowerLimit=0.;
        #upperLimit=1.;
        #ClopperPearsonLimits(rrv_number_data.getVal(), rrv_number_data_fail.getVal(), lowerLimit, upperLimit);
        #print lowerLimit, upperLimit;
        #ClopperPearsonLimits(rrv_number_TotalMC.getVal(), rrv_number_TotalMC_fail.getVal(), lowerLimit, upperLimit);
        #print lowerLimit, upperLimit;


    ########## ---------------------------------------------------
    def eventnumber_in_signalregion(self, label, model_ttbar_data, rfresult):# to get event number in mj signalregion
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");
        rdataset_data_mj = self.workspace4fit_.data("rdataset"+label+"_"+self.channel+"_mj"); 

        rrv_number_ttbar_data=self.workspace4fit_.var("rrv_number_ttbar"+label+"_"+self.channel+"_mj");
        rrv_number_ttbar_data.Print();

        # to calculate the TTbar's normalization and error in M_J signal_region. The error must contain the shape error
        fullInt_data   = model_ttbar_data.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j) );
        signalInt_data = model_ttbar_data.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("signal_region"));
        fullInt_val_data=fullInt_data.getVal();
        signalInt_val_data=signalInt_data.getVal()/fullInt_val_data;
        rrv_number_TTbar_in_mj_signal_region_from_fitting=RooRealVar("rrv_number_ttbar_in_mj_signal_region_from_fitting"+label+"_"+self.channel,"rrv_number_ttbar_in_mj_signal_region_from_fitting"+label+"_"+self.channel,rrv_number_ttbar_data.getVal()*signalInt_val_data);
        #error
        rrv_number_TTbar_in_mj_signal_region_from_fitting.setError( Calc_error_extendPdf(rdataset_data_mj, model_ttbar_data, rfresult,"signal_region") );
        rrv_number_TTbar_in_mj_signal_region_from_fitting.Print();
        getattr(self.workspace4fit_,"import")(rrv_number_TTbar_in_mj_signal_region_from_fitting);



    ########## ---------------------------------------------------
    def get_mj_and_mlvj_dataset(self,in_file_name, label, jet_mass="jet_mass_pr"):# to get the shape of m_lvj
        # read in tree
        fileIn_name=TString(self.file_Directory+in_file_name);
        fileIn = TFile(fileIn_name.Data());
        treeIn = fileIn.Get("otree");
        
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j") 
        rrv_mass_lvj = self.workspace4fit_.var("rrv_mass_lvj") 
        rrv_weight = RooRealVar("rrv_weight","rrv_weight",0. ,10000000.) 
        #dataset of m_j
        rdataset_mj     = RooDataSet("rdataset"+label+"_"+self.channel+"_mj","rdataset"+label+"_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        rdataset4fit_mj = RooDataSet("rdataset4fit"+label+"_"+self.channel+"_mj","rdataset4fit"+label+"_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        #dataset of m_lvj
        rdataset_sb_lo_mlvj         = RooDataSet("rdataset"+label+"_sb_lo"+"_"+self.channel+"_mlvj","rdataset"+label+"_sb_lo"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset_signal_region_mlvj = RooDataSet("rdataset"+label+"_signal_region"+"_"+self.channel+"_mlvj","rdataset"+label+"_signal_region"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset_sb_hi_mlvj         = RooDataSet("rdataset"+label+"_sb_hi"+"_"+self.channel+"_mlvj","rdataset"+label+"_sb_hi"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset4fit_sb_lo_mlvj     = RooDataSet("rdataset4fit"+label+"_sb_lo"+"_"+self.channel+"_mlvj","rdataset4fit"+label+"_sb_lo"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset4fit_signal_region_mlvj = RooDataSet("rdataset4fit"+label+"_signal_region"+"_"+self.channel+"_mlvj","rdataset4fit"+label+"_signal_region"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset4fit_sb_hi_mlvj     = RooDataSet("rdataset4fit"+label+"_sb_hi"+"_"+self.channel+"_mlvj","rdataset4fit"+label+"_sb_hi"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 

        rdataset4fit_sb_lo_mlvj.Print();
        rdataset4fit_signal_region_mlvj.Print();
        data_category=RooCategory("data_category","data_category");
        data_category.defineType("sideband");
        data_category.defineType("signal_region");
        combData=RooDataSet("combData"+label+"_"+self.channel,"combData"+label+"_"+self.channel,RooArgSet(rrv_mass_lvj, data_category, rrv_weight),RooFit.WeightVar(rrv_weight) );
        combData4fit=RooDataSet("combData4fit"+label+"_"+self.channel,"combData4fit"+label+"_"+self.channel,RooArgSet(rrv_mass_lvj, data_category, rrv_weight),RooFit.WeightVar(rrv_weight) );

        print "N entries: ", treeIn.GetEntries()
        hnum_4region=TH1D("hnum_4region"+label+"_"+self.channel,"hnum_4region"+label+"_"+self.channel,4,-1.5,2.5);# m_j   -1: sb_lo; 0:signal_region; 1: sb_hi; 2:total
        hnum_2region=TH1D("hnum_2region"+label+"_"+self.channel,"hnum_2region"+label+"_"+self.channel,2,-0.5,1.5);# m_lvj  0: signal_region; 1: total
        for i in range(treeIn.GetEntries()):
            if i % 10000 == 0: print "i: ",i
            treeIn.GetEntry(i);
            if i==0:
                tmp_scale_to_lumi=treeIn.wSampleWeight;
    
            discriminantCut = False; 

            wtagger=-1;
            wtagger=treeIn.jet_tau2tau1;
            if wtagger <self.wtagger_cut:
                discriminantCut=True;
            else:
                discriminantCut=False;

            #jet mass, jet mass up, jet mass down
            tmp_jet_mass=getattr(treeIn, jet_mass);

            if treeIn.ungroomed_jet_pt > 200. and discriminantCut and tmp_jet_mass >= rrv_mass_j.getMin() and tmp_jet_mass<=rrv_mass_j.getMax() and treeIn.nbjetsSSVHE < 1 and treeIn.mass_lvj >= rrv_mass_lvj.getMin() and treeIn.mass_lvj<=rrv_mass_lvj.getMax() and  treeIn.nPV >=self.nPV_min and treeIn.nPV<=self.nPV_max and treeIn.v_pt > self.vpt_cut and treeIn.pfMET > self.pfMET_cut and treeIn.l_pt > self.lpt_cut:
                #print tmp_jet_mass_dn, tmp_jet_mass, tmp_jet_mass_up;
                tmp_event_weight= treeIn.totalEventWeight;
                tmp_event_weight4fit= treeIn.eff_and_pu_Weight;
                tmp_interference_weight_H600=treeIn.interference_Weight_H600;
                tmp_interference_weight_H700=treeIn.interference_Weight_H700;
                tmp_interference_weight_H800=treeIn.interference_Weight_H800;
                tmp_interference_weight_H900=treeIn.interference_Weight_H900;
                tmp_interference_weight_H1000=treeIn.interference_Weight_H1000;
                ## added by Nhan, getting additional BSM weight
                bsmWeightName = "bsmReweight_cPrime%02d_brNew%02d"%(options.cprime,options.BRnew);
                tmp_bsmWeight = getattr(treeIn, bsmWeightName);
                if tmp_bsmWeight < 0: tmp_bsmWeight = 1;

                if TString(label).Contains("ggH600"): 
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H600
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H600
                if TString(label).Contains("ggH700"): 
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H700
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H700
                if TString(label).Contains("ggH800"): 
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H800
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H800
                if TString(label).Contains("ggH900"): 
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H900
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H900
                if TString(label).Contains("ggH1000"): 
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H1000
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H1000

                if TString(label).Contains("vbfH600"): 
                    tmp_event_weight    =tmp_event_weight*treeIn.cps_Weight_H600;
                    tmp_event_weight4fit=tmp_event_weight4fit*treeIn.cps_Weight_H600;
                if TString(label).Contains("vbfH700"): 
                    tmp_event_weight    =tmp_event_weight*treeIn.cps_Weight_H700;
                    tmp_event_weight4fit=tmp_event_weight4fit*treeIn.cps_Weight_H700;
                if TString(label).Contains("vbfH800"): 
                    tmp_event_weight    =tmp_event_weight*treeIn.cps_Weight_H800;
                    tmp_event_weight4fit=tmp_event_weight4fit*treeIn.cps_Weight_H800;
                if TString(label).Contains("vbfH900"): 
                    tmp_event_weight    =tmp_event_weight*treeIn.cps_Weight_H900;
                    tmp_event_weight4fit=tmp_event_weight4fit*treeIn.cps_Weight_H900;
                if TString(label).Contains("vbfH1000"): 
                    tmp_event_weight    =tmp_event_weight*treeIn.cps_Weight_H1000;
                    tmp_event_weight4fit=tmp_event_weight4fit*treeIn.cps_Weight_H1000;
 
                # for multi-sample, like STop and VV. There are two sample, and two wSampleWeight_value.Use the least wSampleWeight as scale. 
                tmp_event_weight4fit=tmp_event_weight4fit*treeIn.wSampleWeight/tmp_scale_to_lumi

                if TString(label).Contains("ggH"):
                    tmp_event_weight=tmp_event_weight/self.higgs_xs_scale; 
                    tmp_event_weight4fit=tmp_event_weight4fit/self.higgs_xs_scale; 
                    ## added by Nhan
                    tmp_event_weight=tmp_event_weight*tmp_bsmWeight;
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_bsmWeight;

                if TString(label).Contains("vbfH"):
                    tmp_event_weight=tmp_event_weight/self.higgs_xs_scale; 
                    tmp_event_weight4fit=tmp_event_weight4fit/self.higgs_xs_scale; 

                #wtagger_eff_reweight
                if not label=="_data": 
                    if TString(label).Contains("_TTbar") or TString(label).Contains("_STop") :
                        #print label+" SF %s"%(self.rrv_wtagger_eff_reweight_forTop.getVal()) ;
                        tmp_event_weight=tmp_event_weight*self.rrv_wtagger_eff_reweight_forTop.getVal();
                    else:
                        #print label+" SF %s"%(self.rrv_wtagger_eff_reweight_forV.getVal()) ;
                        tmp_event_weight=tmp_event_weight*self.rrv_wtagger_eff_reweight_forV.getVal();
                    tmp_event_weight=tmp_event_weight*self.btag_scale;
                
                rrv_mass_lvj.setVal(treeIn.mass_lvj);
                if tmp_jet_mass >= self.mj_sideband_lo_min and tmp_jet_mass < self.mj_sideband_lo_max:
                    rdataset_sb_lo_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight );
                    rdataset4fit_sb_lo_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight4fit );
                    data_category.setLabel("sideband"); 
                    combData.add(RooArgSet(rrv_mass_lvj,data_category),tmp_event_weight);
                    combData4fit.add(RooArgSet(rrv_mass_lvj,data_category),tmp_event_weight4fit);
                if tmp_jet_mass >= self.mj_signal_min      and tmp_jet_mass < self.mj_signal_max:
                    rdataset_signal_region_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight );
                    rdataset4fit_signal_region_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight4fit );
                    data_category.setLabel("signal_region");
                    combData.add(RooArgSet(rrv_mass_lvj,data_category),tmp_event_weight);
                    combData4fit.add(RooArgSet(rrv_mass_lvj,data_category),tmp_event_weight4fit);
                    hnum_2region.Fill(1,tmp_event_weight);
                    if treeIn.mass_lvj >=self.mlvj_signal_min  and treeIn.mass_lvj <self.mlvj_signal_max: hnum_2region.Fill(0,tmp_event_weight);
                if tmp_jet_mass >= self.mj_sideband_hi_min and tmp_jet_mass < self.mj_sideband_hi_max:
                    rdataset_sb_hi_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight );
                    rdataset4fit_sb_hi_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight4fit );

                rrv_mass_j.setVal( tmp_jet_mass );
                rdataset_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight );
                rdataset4fit_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight4fit );
                if tmp_jet_mass >=self.mj_sideband_lo_min and tmp_jet_mass <self.mj_sideband_lo_max: hnum_4region.Fill(-1,tmp_event_weight );
                if tmp_jet_mass >=self.mj_signal_min      and tmp_jet_mass <self.mj_signal_max     : hnum_4region.Fill(0,tmp_event_weight);
                if tmp_jet_mass >=self.mj_sideband_hi_min and tmp_jet_mass <self.mj_sideband_hi_max: hnum_4region.Fill(1,tmp_event_weight);
                hnum_4region.Fill(2,tmp_event_weight);

        if not label=="_data": 
            if TString(label).Contains("_TTbar") or TString(label).Contains("_STop") :
                tmp_scale_to_lumi=tmp_scale_to_lumi*self.rrv_wtagger_eff_reweight_forTop.getVal();
            else:
                tmp_scale_to_lumi=tmp_scale_to_lumi*self.rrv_wtagger_eff_reweight_forV.getVal();
            tmp_scale_to_lumi=tmp_scale_to_lumi*self.btag_scale;

        rrv_scale_to_lumi=RooRealVar("rrv_scale_to_lumi"+label+"_"+self.channel,"rrv_scale_to_lumi"+label+"_"+self.channel,tmp_scale_to_lumi)
        rrv_scale_to_lumi.Print()
        getattr(self.workspace4fit_,"import")(rrv_scale_to_lumi)
        #prepare m_lvj dataset
        rrv_number_dataset_signal_region_mlvj=RooRealVar("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj","rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj",hnum_2region.GetBinContent(1));
        rrv_number_dataset_AllRange_mlvj=RooRealVar("rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj","rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj",hnum_2region.GetBinContent(2));
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_mlvj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_AllRange_mlvj)
               
        getattr(self.workspace4fit_,"import")(rdataset_sb_lo_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset_signal_region_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset_sb_hi_mlvj); 
        getattr(self.workspace4fit_,"import")(rdataset4fit_sb_lo_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset4fit_signal_region_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset4fit_sb_hi_mlvj);
        getattr(self.workspace4fit_,"import")(combData);
        getattr(self.workspace4fit_,"import")(combData4fit);
        self.file_out.write("\n%s events number in m_lvj from dataset: %s"%(label,rdataset_signal_region_mlvj.sumEntries()))
        #prepare m_j dataset
        rrv_number_dataset_sb_lo_mj=RooRealVar("rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj","rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj",hnum_4region.GetBinContent(1));
        rrv_number_dataset_signal_region_mj=RooRealVar("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj","rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj",hnum_4region.GetBinContent(2));
        rrv_number_dataset_sb_hi_mj=RooRealVar("rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj","rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj",hnum_4region.GetBinContent(3));
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_sb_lo_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_sb_hi_mj)
                
        print "N_rdataset_mj: "
        getattr(self.workspace4fit_,"import")(rdataset_mj)
        getattr(self.workspace4fit_,"import")(rdataset4fit_mj)

        rdataset_sb_lo_mlvj.Print();
        rdataset_signal_region_mlvj.Print();
        rdataset_sb_hi_mlvj.Print();
        rdataset_mj.Print();
        rdataset4fit_sb_lo_mlvj.Print();
        rdataset4fit_signal_region_mlvj.Print();
        rdataset4fit_sb_hi_mlvj.Print();
        rdataset4fit_mj.Print();
        rrv_number_dataset_signal_region_mlvj.Print()
        rrv_number_dataset_AllRange_mlvj.Print()
        rrv_number_dataset_sb_lo_mj.Print()
        rrv_number_dataset_signal_region_mj.Print()
        rrv_number_dataset_sb_hi_mj.Print()
        print rdataset_signal_region_mlvj.sumEntries()
        print rrv_number_dataset_signal_region_mlvj.getVal()
        print rrv_number_dataset_AllRange_mlvj.getVal()
        #raw_input("ENTER");

    ########## ---------------------------------------------------
    def get_mj_and_mlvj_dataset_TTbar_controlsample(self,in_file_name, label, jet_mass="ttb_ca8_mass_pr"):# to get the shape of m_lvj
        # read in tree
        fileIn_name=TString(self.file_Directory+in_file_name);
        fileIn = TFile(fileIn_name.Data());
        treeIn = fileIn.Get("otree");
        
        # define bdt reader
            
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j") 
        rrv_mass_lvj = self.workspace4fit_.var("rrv_mass_lvj") 
        rrv_weight = RooRealVar("rrv_weight","rrv_weight",0. ,10000000.) 
        #dataset of m_j pass tau2tau1 cut
        rdataset_mj = RooDataSet("rdataset"+label+"_"+self.channel+"_mj","rdataset"+label+"_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        rdataset4fit_mj = RooDataSet("rdataset4fit"+label+"_"+self.channel+"_mj","rdataset4fit"+label+"_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        #dataset of m_j before tau2tau1 cut
        rdataset_beforetau2tau1cut_mj = RooDataSet("rdataset"+label+"_beforetau2tau1cut_"+self.channel+"_mj","rdataset"+label+"_beforetau2tau1cut_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        rdataset4fit_beforetau2tau1cut_mj = RooDataSet("rdataset4fit"+label+"_beforetau2tau1cut_"+self.channel+"_mj","rdataset4fit"+label+"_beforetau2tau1cut_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        #dataset of m_j failed tau2tau1 cut
        rdataset_failtau2tau1cut_mj = RooDataSet("rdataset"+label+"_failtau2tau1cut_"+self.channel+"_mj","rdataset"+label+"_failtau2tau1cut_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        rdataset4fit_failtau2tau1cut_mj = RooDataSet("rdataset4fit"+label+"_failtau2tau1cut_"+self.channel+"_mj","rdataset4fit"+label+"_failtau2tau1cut_"+self.channel+"_mj",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight) );
        #dataset of m_lvj
        rdataset_sb_lo_mlvj  = RooDataSet("rdataset"+label+"_sb_lo"+"_"+self.channel+"_mlvj","rdataset"+label+"_sb_lo"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset_signal_region_mlvj = RooDataSet("rdataset"+label+"_signal_region"+"_"+self.channel+"_mlvj","rdataset"+label+"_signal_region"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset_sb_hi_mlvj  = RooDataSet("rdataset"+label+"_sb_hi"+"_"+self.channel+"_mlvj","rdataset"+label+"_sb_hi"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset4fit_sb_lo_mlvj  = RooDataSet("rdataset4fit"+label+"_sb_lo"+"_"+self.channel+"_mlvj","rdataset4fit"+label+"_sb_lo"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset4fit_signal_region_mlvj = RooDataSet("rdataset4fit"+label+"_signal_region"+"_"+self.channel+"_mlvj","rdataset4fit"+label+"_signal_region"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 
        rdataset4fit_sb_hi_mlvj  = RooDataSet("rdataset4fit"+label+"_sb_hi"+"_"+self.channel+"_mlvj","rdataset4fit"+label+"_sb_hi"+"_"+self.channel+"_mlvj",RooArgSet(rrv_mass_lvj,rrv_weight),RooFit.WeightVar(rrv_weight) ); 

        #combine of dataset before and after tau2tau1 cut
        category_cut=RooCategory("category_cut","category_cut");
        category_cut.defineType("cut",1);
        category_cut.defineType("beforecut",2);
        combData4cut=RooDataSet("combData4cut"+label+"_"+self.channel,"combData4cut"+label+"_"+self.channel,RooArgSet(rrv_mass_j, category_cut, rrv_weight),RooFit.WeightVar(rrv_weight) );

        #combine of dataset pass and fail tau2tau1 cut
        if self.workspace4fit_.cat("category_p_f_"+self.channel):
            category_p_f=self.workspace4fit_.cat("category_p_f_"+self.channel);
        else:
            category_p_f=RooCategory("category_p_f_"+self.channel,"category_p_f"+self.channel);
            category_p_f.defineType("pass");
            category_p_f.defineType("fail");
            getattr(self.workspace4fit_,"import")(category_p_f);
        combData_p_f=RooDataSet("combData_p_f"+label+"_"+self.channel,"combData_p_f"+label+"_"+self.channel,RooArgSet(rrv_mass_j, category_p_f, rrv_weight),RooFit.WeightVar(rrv_weight) );


        # make cuts (including mass drop) # create a RooDataSet
        print "N entries: ", treeIn.GetEntries()
        hnum_4region=TH1D("hnum_4region"+label+"_"+self.channel,"hnum_4region"+label+"_"+self.channel,4,-1.5,2.5);# m_j   -1: sb_lo; 0:signal_region; 1: sb_hi; 2:total
        hnum_4region_error2=TH1D("hnum_4region_error2"+label+"_"+self.channel,"hnum_4region_error2"+label+"_"+self.channel,4,-1.5,2.5);# m_j   -1: sb_lo; 0:signal_region; 1: sb_hi; 2:total
        hnum_4region_before_mva=TH1D("hnum_4region_before_mva"+label+"_"+self.channel,"hnum_4region_before_mva"+label+"_"+self.channel,4,-1.5,2.5);# m_j   -1: sb_lo; 0:signal_region; 1: sb_hi; 2:total
        hnum_4region_before_mva_error2=TH1D("hnum_4region_before_mva_error2"+label+"_"+self.channel,"hnum_4region_before_mva_error2"+label+"_"+self.channel,4,-1.5,2.5);# m_j   -1: sb_lo; 0:signal_region; 1: sb_hi; 2:total
        hnum_2region=TH1D("hnum_2region"+label+"_"+self.channel,"hnum_2region"+label+"_"+self.channel,2,-0.5,1.5);# m_lvj  0: signal_region; 1: total
        hnum_2region_error2=TH1D("hnum_2region_error2"+label+"_"+self.channel,"hnum_2region_error2"+label+"_"+self.channel,2,-0.5,1.5);# m_lvj  0: signal_region; 1: total
        for i in range(treeIn.GetEntries()):
            if i % 10000 == 0: print "i: ",i
            treeIn.GetEntry(i);
            if i==0: tmp_scale_to_lumi=treeIn.wSampleWeight;
    
            discriminantCut = False; 

            wtagger=-1;
            #            wtagger=treeIn.jet_tau2tau1;
            wtagger=treeIn.ttb_ca8_tau2tau1
            if wtagger <self.wtagger_cut:
                discriminantCut=True;
            else:
                discriminantCut=False;
            
            tmp_jet_mass=getattr(treeIn, jet_mass);

            if discriminantCut and treeIn.mass_lvj > 0 and (treeIn.ttb_nak5_same_csvm > 0 or treeIn.ttb_nak5_oppoveto_csvm > 0)  and treeIn.isttbar > 0 and treeIn.v_pt > self.vpt_cut and treeIn.l_pt >= self.lpt_cut and treeIn.pfMET > self.pfMET_cut and treeIn.ttb_ca8_ungroomed_pt > 200 and tmp_jet_mass>rrv_mass_j.getMin() and tmp_jet_mass<rrv_mass_j.getMax():

                tmp_event_weight= treeIn.totalEventWeight;
                tmp_event_weight4fit= treeIn.eff_and_pu_Weight;
                tmp_interference_weight_H600=treeIn.interference_Weight_H600;
                tmp_interference_weight_H700=treeIn.interference_Weight_H700;
                tmp_interference_weight_H800=treeIn.interference_Weight_H800;
                tmp_interference_weight_H900=treeIn.interference_Weight_H900;
                tmp_interference_weight_H1000=treeIn.interference_Weight_H1000;
                if label=="_ggH600": 
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H600
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H600
                if label=="_ggH700":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H700
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H700
                if label=="_ggH800":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H800
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H800
                if label=="_ggH900":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H900
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H900
                if label=="_ggH1000":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H1000
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H1000
                # for multi-sample, like STop and VV. There are two sample, and two wSampleWeight_value.Use the least wSampleWeight as scale. 
                tmp_event_weight4fit=tmp_event_weight4fit*treeIn.wSampleWeight/tmp_scale_to_lumi

                rrv_mass_lvj.setVal(treeIn.mass_lvj);
                if tmp_jet_mass >= self.mj_sideband_lo_min and tmp_jet_mass < self.mj_sideband_lo_max:
                    rdataset_sb_lo_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight );
                    rdataset4fit_sb_lo_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight4fit );
                if tmp_jet_mass >= self.mj_signal_min      and tmp_jet_mass < self.mj_signal_max:
                    rdataset_signal_region_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight );
                    rdataset4fit_signal_region_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight4fit );
                    hnum_2region.Fill(1,tmp_event_weight);
                    if treeIn.mass_lvj >=self.mlvj_signal_min  and treeIn.mass_lvj <self.mlvj_signal_max: hnum_2region.Fill(0,tmp_event_weight);
                if tmp_jet_mass >= self.mj_sideband_hi_min and tmp_jet_mass < self.mj_sideband_hi_max:
                    rdataset_sb_hi_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight );
                    rdataset4fit_sb_hi_mlvj.add( RooArgSet( rrv_mass_lvj ), tmp_event_weight4fit );

                rrv_mass_j.setVal( tmp_jet_mass );
                rdataset_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight );
                rdataset4fit_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight4fit );
                if tmp_jet_mass >=self.mj_sideband_lo_min and tmp_jet_mass <self.mj_sideband_lo_max: hnum_4region.Fill(-1,tmp_event_weight );
                if tmp_jet_mass >=self.mj_signal_min      and tmp_jet_mass <self.mj_signal_max     :
                    hnum_4region.Fill(0,tmp_event_weight);
                    hnum_4region_error2.Fill(0,tmp_event_weight*tmp_event_weight);
                if tmp_jet_mass >=self.mj_sideband_hi_min and tmp_jet_mass <self.mj_sideband_hi_max: hnum_4region.Fill(1,tmp_event_weight);
                hnum_4region.Fill(2,tmp_event_weight);
                category_cut.setLabel("cut"); combData4cut.add(RooArgSet(rrv_mass_j,category_cut),tmp_event_weight4fit);
                #category_cut.setLabel("cut"); combData4cut.add(RooArgSet(rrv_mass_j,category_cut),tmp_event_weight);
                category_p_f.setLabel("pass"); combData_p_f.add(RooArgSet(rrv_mass_j,category_p_f),tmp_event_weight);
                #category_p_f.setLabel("pass"); combData_p_f.add(RooArgSet(rrv_mass_j,category_p_f),tmp_event_weight4fit);

            if treeIn.mass_lvj > 0 and (treeIn.ttb_nak5_same_csvm > 0 or treeIn.ttb_nak5_oppoveto_csvm > 0)  and treeIn.isttbar > 0 and treeIn.v_pt >  self.vpt_cut and treeIn.l_pt >= self.lpt_cut and treeIn.pfMET > self.pfMET_cut and treeIn.ttb_ca8_ungroomed_pt > 200 and tmp_jet_mass>rrv_mass_j.getMin() and tmp_jet_mass<rrv_mass_j.getMax():

                tmp_event_weight= treeIn.totalEventWeight;
                tmp_event_weight4fit= treeIn.eff_and_pu_Weight;
                tmp_interference_weight_H600=treeIn.interference_Weight_H600;
                tmp_interference_weight_H700=treeIn.interference_Weight_H700;
                tmp_interference_weight_H800=treeIn.interference_Weight_H800;
                tmp_interference_weight_H900=treeIn.interference_Weight_H900;
                tmp_interference_weight_H1000=treeIn.interference_Weight_H1000;
                if label=="_ggH600":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H600
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H600
                if label=="_ggH700":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H700
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H700
                if label=="_ggH800":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H800
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H800
                if label=="_ggH900":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H900
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H900
                if label=="_ggH1000":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H1000
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H1000
                tmp_event_weight4fit=tmp_event_weight4fit*treeIn.wSampleWeight/tmp_scale_to_lumi
                rrv_mass_lvj.setVal(treeIn.mass_lvj);

                if tmp_jet_mass >=self.mj_signal_min      and tmp_jet_mass <self.mj_signal_max     :
                    hnum_4region_before_mva.Fill(0,tmp_event_weight);
                    hnum_4region_before_mva_error2.Fill(0,tmp_event_weight*tmp_event_weight);
                rrv_mass_j.setVal( tmp_jet_mass );
                rdataset_beforetau2tau1cut_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight );
                rdataset4fit_beforetau2tau1cut_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight4fit );

                category_cut.setLabel("beforecut"); combData4cut.add(RooArgSet(rrv_mass_j,category_cut),tmp_event_weight4fit);
                #category_cut.setLabel("beforecut"); combData4cut.add(RooArgSet(rrv_mass_j,category_cut),tmp_event_weight);

            if (not discriminantCut) and treeIn.mass_lvj > 0 and (treeIn.ttb_nak5_same_csvm > 0 or treeIn.ttb_nak5_oppoveto_csvm > 0)  and treeIn.isttbar > 0 and treeIn.v_pt >  self.vpt_cut and treeIn.l_pt >= self.lpt_cut and treeIn.pfMET > self.pfMET_cut and treeIn.ttb_ca8_ungroomed_pt > 200 and tmp_jet_mass>rrv_mass_j.getMin() and tmp_jet_mass<rrv_mass_j.getMax():

                tmp_event_weight= treeIn.totalEventWeight;
                tmp_event_weight4fit= treeIn.eff_and_pu_Weight;
                tmp_interference_weight_H600=treeIn.interference_Weight_H600;
                tmp_interference_weight_H700=treeIn.interference_Weight_H700;
                tmp_interference_weight_H800=treeIn.interference_Weight_H800;
                tmp_interference_weight_H900=treeIn.interference_Weight_H900;
                tmp_interference_weight_H1000=treeIn.interference_Weight_H1000;
                if label=="_ggH600":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H600
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H600
                if label=="_ggH700":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H700
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H700
                if label=="_ggH800":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H800
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H800
                if label=="_ggH900":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H900
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H900
                if label=="_ggH1000":
                    tmp_event_weight=tmp_event_weight*tmp_interference_weight_H1000
                    tmp_event_weight4fit=tmp_event_weight4fit*tmp_interference_weight_H1000
                tmp_event_weight4fit=tmp_event_weight4fit*treeIn.wSampleWeight/tmp_scale_to_lumi
                rrv_mass_lvj.setVal(treeIn.mass_lvj);

                rrv_mass_j.setVal( tmp_jet_mass );
                rdataset_failtau2tau1cut_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight );
                rdataset4fit_failtau2tau1cut_mj.add( RooArgSet( rrv_mass_j ), tmp_event_weight4fit );
                category_p_f.setLabel("fail"); combData_p_f.add(RooArgSet(rrv_mass_j,category_p_f),tmp_event_weight);
                #category_p_f.setLabel("fail"); combData_p_f.add(RooArgSet(rrv_mass_j,category_p_f),tmp_event_weight4fit);

        rrv_scale_to_lumi=RooRealVar("rrv_scale_to_lumi"+label+"_"+self.channel,"rrv_scale_to_lumi"+label+"_"+self.channel,tmp_scale_to_lumi);# rrv_scale_to_lumi.Print()
        rrv_scale_to_lumi_failtau2tau1cut=RooRealVar("rrv_scale_to_lumi"+label+"_failtau2tau1cut_"+self.channel,"rrv_scale_to_lumi"+label+"_failtau2tau1cut_"+self.channel,tmp_scale_to_lumi);# rrv_scale_to_lumi.Print()
        getattr(self.workspace4fit_,"import")(rrv_scale_to_lumi)
        getattr(self.workspace4fit_,"import")(rrv_scale_to_lumi_failtau2tau1cut)
        #prepare m_lvj dataset
        rrv_number_dataset_signal_region_mlvj=RooRealVar("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj","rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj",hnum_2region.GetBinContent(1));
        rrv_number_dataset_AllRange_mlvj=RooRealVar("rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj","rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj",hnum_2region.GetBinContent(2));
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_mlvj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_AllRange_mlvj)
               
        getattr(self.workspace4fit_,"import")(rdataset_sb_lo_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset_signal_region_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset_sb_hi_mlvj); 
        getattr(self.workspace4fit_,"import")(rdataset4fit_sb_lo_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset4fit_signal_region_mlvj);
        getattr(self.workspace4fit_,"import")(rdataset4fit_sb_hi_mlvj);
        getattr(self.workspace4fit_,"import")(combData4cut);
        getattr(self.workspace4fit_,"import")(combData_p_f);
        self.file_out.write("\n%s events number in m_lvj from dataset: %s"%(label,rdataset_signal_region_mlvj.sumEntries()))
        #prepare m_j dataset
        rrv_number_dataset_sb_lo_mj=RooRealVar("rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj","rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj",hnum_4region.GetBinContent(1));
        rrv_number_dataset_signal_region_mj=RooRealVar("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj","rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj",hnum_4region.GetBinContent(2));
        rrv_number_dataset_signal_region_error2_mj=RooRealVar("rrv_number_dataset_signal_region_error2"+label+"_"+self.channel+"_mj","rrv_number_dataset_signal_region_error2"+label+"_"+self.channel+"_mj",hnum_4region_error2.GetBinContent(2));
        rrv_number_dataset_signal_region_before_mva_mj=RooRealVar("rrv_number_dataset_signal_region_before_mva"+label+"_"+self.channel+"_mj","rrv_number_dataset_signal_region_before_mva"+label+"_"+self.channel+"_mj",hnum_4region_before_mva.GetBinContent(2));
        rrv_number_dataset_signal_region_before_mva_error2_mj=RooRealVar("rrv_number_dataset_signal_region_before_mva_error2"+label+"_"+self.channel+"_mj","rrv_number_dataset_signal_region_before_mva_error2"+label+"_"+self.channel+"_mj",hnum_4region_before_mva_error2.GetBinContent(2));
        rrv_number_dataset_sb_hi_mj=RooRealVar("rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj","rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj",hnum_4region.GetBinContent(3));
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_sb_lo_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_error2_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_before_mva_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_signal_region_before_mva_error2_mj)
        getattr(self.workspace4fit_,"import")(rrv_number_dataset_sb_hi_mj)
                
        print "N_rdataset_mj: "
        getattr(self.workspace4fit_,"import")(rdataset_mj)
        getattr(self.workspace4fit_,"import")(rdataset4fit_mj)
        getattr(self.workspace4fit_,"import")(rdataset_beforetau2tau1cut_mj)
        getattr(self.workspace4fit_,"import")(rdataset4fit_beforetau2tau1cut_mj)
        getattr(self.workspace4fit_,"import")(rdataset_failtau2tau1cut_mj)
        getattr(self.workspace4fit_,"import")(rdataset4fit_failtau2tau1cut_mj)

        rdataset_sb_lo_mlvj.Print();
        rdataset_signal_region_mlvj.Print();
        rdataset_sb_hi_mlvj.Print();
        rdataset_mj.Print();
        rdataset4fit_sb_lo_mlvj.Print();
        rdataset4fit_signal_region_mlvj.Print();
        rdataset4fit_sb_hi_mlvj.Print();
        rdataset4fit_mj.Print();
        rrv_number_dataset_signal_region_mlvj.Print()
        rrv_number_dataset_AllRange_mlvj.Print()
        rrv_number_dataset_sb_lo_mj.Print()
        rrv_number_dataset_signal_region_mj.Print()
        rrv_number_dataset_signal_region_before_mva_mj.Print()
        rrv_number_dataset_sb_hi_mj.Print()
        print rdataset_signal_region_mlvj.sumEntries()
        print rrv_number_dataset_signal_region_mlvj.getVal()
        print rrv_number_dataset_AllRange_mlvj.getVal()

    ######## ++++++++++++++
    def saveHist(self, label):
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");
        rdataset_pass=self.workspace4fit_.data("rdataset"+label+"_"+self.channel+"_mj")
        rdataset_fail=self.workspace4fit_.data("rdataset"+label+"_failtau2tau1cut_"+self.channel+"_mj")
        hist_pass=self.change_dataset_to_histogram(rrv_mass_j,rdataset_pass,"pass"+label+"_"+self.channel);
        hist_fail=self.change_dataset_to_histogram(rrv_mass_j,rdataset_fail,"fail"+label+"_"+self.channel);
        #rootfile=TFile("histo_ttbarcontrolsample"+label+"_"+self.channel+".root","new");
        rootfile=TFile("histo_ttbarcontrolsample"+label+"_"+self.channel+".root","recreate");
        hist_pass.Write();
        hist_fail.Write();
        rootfile.Close();

    ######## ++++++++++++++
    def ControlPlots(self):
        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && nbjets >=1 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#ttbar control sample
        #self.Make_Controlplots(cut,"ttbar_control_sample");

        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=70 && jet_mass_pr<=100 && nbjets>0 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#before_cut
        #self.Make_Controlplots(cut,"ttbar");

        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=70 && jet_mass_pr<=100  && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#before_cut
        #self.Make_Controlplots(cut,"before_cut");

        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=70 && jet_mass_pr<=100 && nbjets<1 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#before_cut
        #self.Make_Controlplots(cut,"bf_cut");

        cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=70 && jet_mass_pr<=100 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#signal region
        self.Make_Controlplots(cut,"before_nbjet");
        cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=70 && jet_mass_pr<=100 && njets<2 && nbjetsSSVHE <1 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#signal region
        self.Make_Controlplots(cut,"signal_region");

        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=30 && jet_mass_pr<=70 && njets <1 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#sb_lo
        #self.Make_Controlplots(cut,"sd_lo");

        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && jet_mass_pr>=100 && jet_mass_pr<=130 && njets <1 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#sb_hi
        #self.Make_Controlplots(cut,"sd_hi");

        #cut="ungroomed_jet_pt>200 && jet_tau2tau1<0.525 && njets <1 && mass_lvj>400 && mass_lvj <1400 && nPV>=%s && nPV<=%s"%(self.nPV_min,self.nPV_max);#without jet_mass cut
        #self.Make_Controlplots(cut,"all_range");

    ######## ++++++++++++++
    def Make_Controlplots(self,cut,tag):
        self.make_controlplot("mass_lvj",cut,tag,25,400,1400,xtitle="mass(lvj)",ytitle="Events",logy=0 );
        self.make_controlplot("jet_mass_pr",cut,tag,55,0,220,xtitle="mass(j)",ytitle="Events",logy=0 );
        self.make_controlplot("v_pt",cut,tag,40,0, 800,xtitle="v_pt",ytitle="Events",logy=0 );
        self.make_controlplot("l_pt",cut,tag,30,0, 600,xtitle="l_pt",ytitle="Events",logy=0 );
        self.make_controlplot("l_eta",cut,tag,25,-2.5,2.5,xtitle="l_eta",ytitle="Events",logy=0 );
        self.make_controlplot("mvaMET",cut,tag,25,0,500,xtitle="mvaMET",ytitle="Events",logy=0 );
        self.make_controlplot("nPV",cut,tag,40,0,40,xtitle="nPV",ytitle="Events",logy=0 );
        self.make_controlplot("jet_tau2tau1",cut,tag,50,0,1,xtitle="jet_tau2tau1",ytitle="Events",logy=0 );
        self.make_controlplot("nbjets",cut,tag,5,-0.5,4.5,xtitle="number of b-jets",ytitle="Events",logy=0 );
        self.make_controlplot("nbjetsCSV",cut,tag,5,-0.5,4.5,xtitle="number of b-jets(CSV)",ytitle="Events",logy=0 );
        self.make_controlplot("nbjetsSSVHE",cut,tag,5,-0.5,4.5,xtitle="number of b-jets(SSVHE)",ytitle="Events",logy=0 );
        self.make_controlplot("njets",cut,tag,5,-0.5,4.5,xtitle="number of jets",ytitle="Events",logy=0 );
 
    ######## ++++++++++++++
    def make_controlplot(self,variable,cut,tag,nbin,min,max,xtitle="",ytitle="",logy=0 ):
        #weight_mc="totalEventWeight";
        weight_mc="totalEventWeight*%s"%(self.rrv_wtagger_eff_reweight_forV.getVal());#little error rrv_wtagger_eff_reweight_forTop

        weightcut_mc="(%s)*(%s)"%(weight_mc,cut);
        weightcut_data="%s"%(cut);
        print "weightcut_mc="+weightcut_mc;
        hist_data =TH1D("hist_data","hist_data"+";%s;%s"%(xtitle,ytitle),nbin,min,max);
        hist_Signal =TH1D("hist_Signal","hist_Signal"+";%s;%s"%(xtitle,ytitle),nbin,min,max);
        hist_WJets=TH1D("hist_WJets","hist_WJets"+";%s;%s"%(xtitle,ytitle),nbin,min,max);
        hist_TTbar=TH1D("hist_TTbar","hist_TTbar"+";%s;%s"%(xtitle,ytitle),nbin,min,max);
        hist_STop =TH1D("hist_STop","hist_STop"+";%s;%s"%(xtitle,ytitle),nbin,min,max);
        hist_VV   =TH1D("hist_VV","hist_VV"+";%s;%s"%(xtitle,ytitle),nbin,min,max);
        hist_TotalMC =TH1D("hist_TotalMC","hist_TotalMC"+";%s;%s"%(xtitle,ytitle),nbin,min,max);

        hstack_TotalMC = THStack("hstack_TotalMC","hstack_TotalMC"+";%s;%s"%(xtitle,ytitle))
        hstack_TotalMC.Add(hist_STop);
        hstack_TotalMC.Add(hist_TTbar);
        hstack_TotalMC.Add(hist_VV);
        hstack_TotalMC.Add(hist_WJets); 

        hist_data.SetLineColor(self.color_palet["data"]); hist_data.SetFillColor(self.color_palet["data"]);
        hist_Signal.SetLineColor(self.color_palet["Signal"]); hist_Signal.SetFillColor(self.color_palet["Signal"]); hist_Signal.SetFillStyle(0);hist_Signal.SetLineWidth(2);
        hist_WJets.SetLineColor(self.color_palet["WJets"]); hist_WJets.SetFillColor(self.color_palet["WJets"]);
        hist_TTbar.SetLineColor(self.color_palet["TTbar"]); hist_TTbar.SetFillColor(self.color_palet["TTbar"]);
        hist_STop.SetLineColor(self.color_palet["STop"]); hist_STop.SetFillColor(self.color_palet["STop"]);
        hist_VV.SetLineColor(self.color_palet["VV"]); hist_VV.SetFillColor(self.color_palet["VV"]);

        tree_data =TChain("otree");  tree_data.Add(self.file_Directory+self.file_data);
        tree_Signal =TChain("otree");  tree_Signal.Add(self.file_Directory+self.file_ggH);
        tree_WJets =TChain("otree");tree_WJets.Add(self.file_Directory+self.file_WJets0_mc);
        tree_TTbar =TChain("otree");tree_TTbar.Add(self.file_Directory+self.file_TTbar_mc);
        tree_STop =TChain("otree");  tree_STop.Add(self.file_Directory+self.file_STop_mc);
        tree_VV =TChain("otree");      tree_VV.Add(self.file_Directory+self.file_VV_mc);

        tree_data.Draw("%s >> hist_data"%(variable), weightcut_data);
        tree_Signal.Draw("%s >> hist_Signal"%(variable), weightcut_mc);
        tree_WJets.Draw("%s >> hist_WJets"%(variable), weightcut_mc);
        tree_TTbar.Draw("%s >> hist_TTbar"%(variable), weightcut_mc);
        tree_STop.Draw("%s >> hist_STop"%(variable), weightcut_mc);
        tree_VV.Draw("%s >> hist_VV"%(variable), weightcut_mc);

        hist_TotalMC.Add(hist_WJets); hist_TotalMC.Add(hist_TTbar); hist_TotalMC.Add(hist_STop); hist_TotalMC.Add(hist_VV);

        canvas_controlplot = TCanvas("canvas_controlplot","canvas_controlplot",1000,800);
        canvas_controlplot.cd();
        hist_data.GetYaxis().SetRangeUser(1e-2,TMath.Max(hist_data.GetMaximum(),hist_TotalMC.GetMaximum())*1.2);
        hist_data.Draw("e");
        hstack_TotalMC.Draw("HIST same");
        hist_data.Draw("same e");
        hist_Signal.Draw("same HIST");

        hist_data.GetXaxis().SetTitleOffset(1.1);
        hist_data.GetYaxis().SetTitleOffset(1.1);
        hist_data.GetXaxis().SetTitleSize(0.04);
        hist_data.GetYaxis().SetTitleSize(0.04);
        hist_data.GetXaxis().SetLabelSize(0.04);
        hist_data.GetYaxis().SetLabelSize(0.04);

        banner = TLatex(0.18,0.96,("CMS Preliminary, %.1f fb^{-1} at #sqrt{s}=8TeV %s+jets"%(self.GetLumi(),self.channel)));
        banner.SetNDC(); banner.SetTextSize(0.028);
        banner.Draw();

        theLeg = TLegend(0.65, 0.57, 0.92, 0.87, "", "NDC");
        theLeg.SetName("theLegend"); theLeg.SetBorderSize(0); theLeg.SetLineColor(0); theLeg.SetFillColor(0);
        theLeg.SetFillStyle(0); theLeg.SetLineWidth(0); theLeg.SetLineStyle(0); theLeg.SetTextFont(42);
        theLeg.SetTextSize(.045);
        
        theLeg.AddEntry(hist_WJets, "WJets","F");
        theLeg.AddEntry(hist_TTbar, "TTbar","F");
        theLeg.AddEntry(hist_STop, "Single-T","F");
        theLeg.AddEntry(hist_VV, "VV","F");
        theLeg.AddEntry(hist_Signal, self.higgs_sample+" #times 50","L");
        theLeg.AddEntry(hist_data, "data","ep");
        theLeg.SetY1NDC(0.9 - 0.05*6 - 0.005);
        theLeg.SetY1(theLeg.GetY1NDC());
        theLeg.Draw();

        Directory=TString("plots_%s_%s/controlplot_wtaggercut%s_nPV%sto%s/"%(self.channel, self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max)+self.higgs_sample+"_%02d_%02d/"%(options.cprime,options.BRnew));
        if not Directory.EndsWith("/"):Directory=Directory.Append("/");
        if not os.path.isdir(Directory.Data()): os.system("mkdir -p  "+Directory.Data());

        rlt_file=TString(Directory.Data()+"controlplot_"+variable+"_"+tag+".png");
        canvas_controlplot.SaveAs(rlt_file.Data());
        rlt_file.ReplaceAll(".png",".eps"); 
        canvas_controlplot.SaveAs(rlt_file.Data());

        if logy:
            canvas_controlplot.SetLogy() ;
            canvas_controlplot.Update();
            rlt_file.ReplaceAll(".eps","_log.eps"); 
            canvas_controlplot.SaveAs(rlt_file.Data());
            rlt_file.ReplaceAll(".eps",".png"); 
            canvas_controlplot.SaveAs(rlt_file.Data());

    ######## ++++++++++++++
    def fit_mlvj_model_single_MC(self,in_file_name, label, in_range, mlvj_model, deco=0):# model = shape + normalization
        rrv_mass_lvj = self.workspace4fit_.var("rrv_mass_lvj") 
        rdataset = self.workspace4fit_.data("rdataset4fit"+label+in_range+"_"+self.channel+"_mlvj"); 
        model = self.make_Model(label+in_range,mlvj_model,"_mlvj");
        model.fitTo( rdataset, RooFit.Save(1), RooFit.SumW2Error(kTRUE) ,RooFit.Extended(kTRUE) );
        rfresult = model.fitTo( rdataset, RooFit.Save(1), RooFit.SumW2Error(kTRUE) ,RooFit.Extended(kTRUE) );
        #rfresult = model.fitTo( rdataset, RooFit.Save(1),RooFit.Extended(kTRUE) );
        rfresult.SetName("rfresult"+label+in_range+"_"+self.channel+"_mlvj")
        getattr(self.workspace4fit_,"import")(rfresult)
        
        mplot = rrv_mass_lvj.frame(RooFit.Title("M_{lvj"+in_range+"} fitted by "+mlvj_model));
        #if label=="_WJets0": mplot.GetYaxis().SetRangeUser(1e-2,310);
        rdataset.plotOn( mplot ,RooFit.DataError(RooAbsData.SumW2) );
        #model.plotOn(mplot,RooFit.VisualizeError(rfresult,1,kFALSE),RooFit.DrawOption("F"),RooFit.FillColor(kOrange), RooFit.VLines());
        #model.plotOn(mplot,RooFit.VisualizeError(rfresult,1),RooFit.FillColor(kOrange), RooFit.VLines());
        if not (TString(label).Contains("ggH") or  TString(label).Contains("vbfH") ): draw_error_band_extendPdf(rdataset, model, rfresult,mplot,6,"L")
        #draw_error_band_extendPdf(rdataset, model, rfresult,mplot,6,"L")
        rdataset.plotOn( mplot ,RooFit.DataError(RooAbsData.SumW2) );
        model.plotOn( mplot , RooFit.VLines());

        if deco :
            model_pdf=self.workspace4fit_.pdf("model_pdf%s%s_%s_mlvj"%(label,in_range,self.channel));
            model_pdf.fitTo( rdataset, RooFit.Save(1), RooFit.SumW2Error(kTRUE) );
            rfresult_pdf=model_pdf.fitTo( rdataset, RooFit.Save(1), RooFit.SumW2Error(kTRUE) );
            wsfit_tmp=RooWorkspace("wsfit_tmp"+label+in_range+"_"+self.channel+"_mlvj");
            Deco=PdfDiagonalizer("Deco"+label+in_range+"_"+self.channel+"_mlvj",wsfit_tmp,rfresult_pdf);
            model_pdf_deco=Deco.diagonalize(model_pdf);
            getattr(self.workspace4fit_,"import")(model_pdf_deco);
            wsfit_tmp.Print("v");
            model_pdf_deco.getParameters(rdataset).Print("v");
            model_pdf.getParameters(rdataset).Print("v");
            model_pdf.Print();
            model_pdf_deco.Print();
            rfresult_pdf.covarianceMatrix().Print();# raw_input("ENTER");
            mplot_deco=rrv_mass_lvj.frame();
            rdataset.plotOn(mplot_deco, RooFit.Name("TTbar MC"));
            model_pdf_deco.plotOn(mplot_deco,RooFit.Name("TTbar"),RooFit.LineColor(kBlack));
            rrv_number_dataset=RooRealVar("rrv_number_dataset","rrv_number_dataset",rdataset.sumEntries());
            rrv_number_dataset.setError(0.)#(rdataset.sumEntries())**0.5);
            draw_error_band(rdataset, model_pdf,rrv_number_dataset,rfresult_pdf,mplot_deco,self.color_palet["Uncertainty"],"F");
            if label=="_TTbar" and in_range=="_signal_region":
                #self.workspace4fit_.pdf("model_TTbar_Powheg_signal_region_%s_mlvj"%(self.channel)).plotOn(mplot_deco,RooFit.Name("TTbar_Powheg"), RooFit.LineStyle(kDashed),RooFit.LineColor(kBlack));
                self.workspace4fit_.pdf("model_TTbar_MG_signal_region_%s_mlvj"%(self.channel)).plotOn(mplot_deco,RooFit.Name("TTbar_MG"), RooFit.LineStyle(kDashed),RooFit.LineColor(kBlack));
                self.workspace4fit_.pdf("model_TTbar_scaleUp_signal_region_%s_mlvj"%(self.channel)).plotOn(mplot_deco,RooFit.Name("TTbar_scaleUp"), RooFit.LineColor(kRed));
                self.workspace4fit_.pdf("model_TTbar_scaleDn_signal_region_%s_mlvj"%(self.channel)).plotOn(mplot_deco,RooFit.Name("TTbar_scaleDn"), RooFit.LineStyle(kDashed),RooFit.LineColor(kRed));
                self.workspace4fit_.pdf("model_TTbar_matchUp_signal_region_%s_mlvj"%(self.channel)).plotOn(mplot_deco,RooFit.Name("TTbar_matchUp"), RooFit.LineColor(kBlue));
                self.workspace4fit_.pdf("model_TTbar_matchDn_signal_region_%s_mlvj"%(self.channel)).plotOn(mplot_deco,RooFit.Name("TTbar_matchDn"), RooFit.LineStyle(kDashed),RooFit.LineColor(kBlue));
                self.workspace4fit_.var("rrv_number_TTbar_matchDn_signal_region_%s_mlvj"%(self.channel)).Print();
                self.workspace4fit_.var("rrv_number_TTbar_matchUp_signal_region_%s_mlvj"%(self.channel)).Print();
                self.workspace4fit_.var("rrv_number_TTbar_scaleDn_signal_region_%s_mlvj"%(self.channel)).Print();
                self.workspace4fit_.var("rrv_number_TTbar_scaleUp_signal_region_%s_mlvj"%(self.channel)).Print();
                #self.workspace4fit_.var("rrv_number_TTbar_Powheg_signal_region_%s_mlvj"%(self.channel)).Print();
                self.workspace4fit_.var("rrv_number_TTbar_MG_signal_region_%s_mlvj"%(self.channel)).Print();
                self.workspace4fit_.var("rrv_number_TTbar_signal_region_%s_mlvj"%(self.channel)).Print();
            leg=self.legend4Plot(mplot_deco,0);
            mplot_deco.addObject(leg);
            self.draw_canvas1( mplot_deco, "plots_%s_%s/other/"%(self.channel,self.PS_model), "m_lvj"+label+in_range+in_range+mlvj_model+"_deco")

        #pull
        hpull=mplot.pullHist();
        mplot_pull = rrv_mass_lvj.frame(RooFit.Title("Pull Distribution"));
        mplot_pull.addPlotable(hpull,"P");
        mplot_pull.SetTitle("PULL");
        mplot_pull.GetYaxis().SetRangeUser(-5,5);
         
        parameters_list=model.getParameters(rdataset);
        mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1);
        self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_lvj_fitting/"%(self.channel,self.PS_model), in_file_name,"m_lvj"+in_range+mlvj_model)
        #rfresult.Print(); rfresult.covarianceMatrix().Print(); raw_input("ENTER");

        #normalize the number of total events to lumi
        #self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").Print()
        #self.workspace4fit_.var("rrv_scale_to_lumi"+label+"_"+self.channel).Print()

        self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").Print();
        self.workspace4fit_.var("rrv_scale_to_lumi"+label+"_"+self.channel).Print()
        self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").setVal( self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").getVal()*self.workspace4fit_.var("rrv_scale_to_lumi"+label+"_"+self.channel).getVal()  )
        self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").setError(self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").getError()*self.workspace4fit_.var("rrv_scale_to_lumi"+label+"_"+self.channel).getVal()  )

        self.workspace4fit_.var("rrv_number"+label+in_range+"_"+self.channel+"_mlvj").Print(); #raw_input("ENTER");

    ######## ++++++++++++++
    def fit_WJetsNorm(self): # to  get the normalization of WJets in signal_region
        self.fit_WJetsNormalization_in_Mj_signal_region("_WJets0");
        self.fit_WJetsNormalization_in_Mj_signal_region("_WJets0massup","massup");
        self.fit_WJetsNormalization_in_Mj_signal_region("_WJets0massdn","massdn");
        self.fit_WJetsNormalization_in_Mj_signal_region("_WJets1");
        self.fit_WJetsNormalization_in_Mj_signal_region("_WJets01");

        rrv_WJets0=self.workspace4fit_.var("rrv_number_WJets0_in_mj_signal_region_from_fitting_%s"%(self.channel));
        rrv_WJets1=self.workspace4fit_.var("rrv_number_WJets1_in_mj_signal_region_from_fitting_%s"%(self.channel));
        rrv_WJets01=self.workspace4fit_.var("rrv_number_WJets01_in_mj_signal_region_from_fitting_%s"%(self.channel));
        rrv_WJets0massup=self.workspace4fit_.var("rrv_number_WJets0massup_in_mj_signal_region_from_fitting_%s"%(self.channel));
        rrv_WJets0massdn=self.workspace4fit_.var("rrv_number_WJets0massdn_in_mj_signal_region_from_fitting_%s"%(self.channel));

        rrv_WJets0.Print();
        rrv_WJets1.Print();
        rrv_WJets01.Print();
        rrv_WJets0massup.Print();
        rrv_WJets0massdn.Print();
        total_uncertainty=TMath.Sqrt( TMath.Power(rrv_WJets0.getError(),2)+ TMath.Power(rrv_WJets1.getVal()-rrv_WJets0.getVal(),2)+ TMath.Power(rrv_WJets01.getVal()-rrv_WJets0.getVal(),2) );
        rrv_WJets0.setError(total_uncertainty);
        rrv_WJets0.Print();

        #jet mass uncertainty on WJets normalization
        self.WJets_normlization_uncertainty_from_jet_mass= ( TMath.Abs(rrv_WJets0massup.getVal()-rrv_WJets0.getVal())+TMath.Abs(rrv_WJets0massdn.getVal()-rrv_WJets0.getVal() ) )/2./rrv_WJets0.getVal();  

        rrv_STop      =self.workspace4fit_.var("rrv_number_dataset_signal_region_STop_%s_mj"%(self.channel))
        rrv_STopmassup=self.workspace4fit_.var("rrv_number_dataset_signal_region_STopmassup_%s_mj"%(self.channel))
        rrv_STopmassdn=self.workspace4fit_.var("rrv_number_dataset_signal_region_STopmassdn_%s_mj"%(self.channel))
        self.STop_normlization_uncertainty_from_jet_mass=( TMath.Abs(rrv_STopmassup.getVal()-rrv_STop.getVal())+TMath.Abs(rrv_STopmassdn.getVal()-rrv_STop.getVal() ) )/2./rrv_STop.getVal();  

        rrv_TTbar      =self.workspace4fit_.var("rrv_number_dataset_signal_region_TTbar_%s_mj"%(self.channel))
        rrv_TTbarmassup=self.workspace4fit_.var("rrv_number_dataset_signal_region_TTbarmassup_%s_mj"%(self.channel))
        rrv_TTbarmassdn=self.workspace4fit_.var("rrv_number_dataset_signal_region_TTbarmassdn_%s_mj"%(self.channel))
        self.TTbar_normlization_uncertainty_from_jet_mass=( TMath.Abs(rrv_TTbarmassup.getVal()-rrv_TTbar.getVal())+TMath.Abs(rrv_TTbarmassdn.getVal()-rrv_TTbar.getVal() ) )/2./rrv_TTbar.getVal();  

        rrv_VV      =self.workspace4fit_.var("rrv_number_dataset_signal_region_VV_%s_mj"%(self.channel))
        rrv_VVmassup=self.workspace4fit_.var("rrv_number_dataset_signal_region_VVmassup_%s_mj"%(self.channel))
        rrv_VVmassdn=self.workspace4fit_.var("rrv_number_dataset_signal_region_VVmassdn_%s_mj"%(self.channel))
        self.VV_normlization_uncertainty_from_jet_mass=( TMath.Abs(rrv_VVmassup.getVal()-rrv_VV.getVal())+TMath.Abs(rrv_VVmassdn.getVal()-rrv_VV.getVal() ) )/2./rrv_VV.getVal();  

        #raw_input("ENTER");
    ######## ++++++++++++++
    def fit_WJetsNormalization_in_Mj_signal_region(self,label,massscale=""): # to  get the normalization of WJets in signal_region
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j") 
        #because the J_mass uncertainty only effect the shape, and the shape effect the WJets final normlization, so only use the rdataset_data_%s_mj, not use rdataset_datamassup rdataset_datamassdn
        rdataset_data_mj=self.workspace4fit_.data("rdataset_data_%s_mj"%(self.channel))

        model_TTbar=self.get_TTbar_mj_Model("_TTbar"+massscale);
        model_STop=self.get_STop_mj_Model("_STop"+massscale);
        model_VV=self.get_VV_mj_Model("_VV"+massscale);
        model_WJets=self.get_WJets_mj_Model(label);
        #model_TTbar.Print(); model_STop.Print(); model_VV.Print(); model_WJets.Print(); raw_input("ENTER");
        model_data=RooAddPdf("model_data%s_%s_mj"%(massscale,self.channel),"model_data%s_%s_mj"%(massscale,self.channel),RooArgList(model_WJets,model_VV,model_TTbar,model_STop));
        # fit the sideband range
        #rfresult = model_data.fitTo( rdataset_data_mj, RooFit.Save(1) , RooFit.Range("sb_lo,sb_hi") ,RooFit.Extended(kTRUE) );
        #rfresult = model_data.fitTo( rdataset_data_mj, RooFit.Save(1) , RooFit.Range("sb_lo,sb_hi") ,RooFit.Extended(kTRUE) );
        rfresult = model_data.fitTo( rdataset_data_mj, RooFit.Save(1) , RooFit.Range("sb_lo,sb_hi") ,RooFit.Extended(kTRUE), RooFit.NumCPU(2) );
        rfresult = model_data.fitTo( rdataset_data_mj, RooFit.Save(1) , RooFit.Range("sb_lo,sb_hi") ,RooFit.Extended(kTRUE), RooFit.NumCPU(2) );
        rfresult.Print(); rfresult.covarianceMatrix().Print();
        getattr(self.workspace4fit_,"import")(model_data);

        rrv_number_data_mj=RooRealVar("rrv_number_data%s_%s_mj"%(massscale,self.channel),"rrv_number_data%s_%s_mj"%(massscale,self.channel), 
                self.workspace4fit_.var("rrv_number_TTbar%s_%s_mj"%(massscale,self.channel)).getVal()+
                self.workspace4fit_.var("rrv_number_STop%s_%s_mj"%(massscale,self.channel)).getVal()+
                self.workspace4fit_.var("rrv_number_VV%s_%s_mj"%(massscale,self.channel)).getVal()+
                self.workspace4fit_.var("rrv_number%s_%s_mj"%(label,self.channel)).getVal()
                );
        rrv_number_data_mj.setError(TMath.Sqrt(
                self.workspace4fit_.var("rrv_number_TTbar%s_%s_mj"%(massscale,self.channel)).getError()*self.workspace4fit_.var("rrv_number_TTbar%s_%s_mj"%(massscale,self.channel)).getError()+
                self.workspace4fit_.var("rrv_number_STop%s_%s_mj"%(massscale,self.channel)).getError()*self.workspace4fit_.var("rrv_number_STop%s_%s_mj"%(massscale,self.channel)).getError()+
                self.workspace4fit_.var("rrv_number_VV%s_%s_mj"%(massscale,self.channel)).getError()*self.workspace4fit_.var("rrv_number_VV%s_%s_mj"%(massscale,self.channel)).getError()+
                self.workspace4fit_.var("rrv_number%s_%s_mj"%(label,self.channel)).getError()*self.workspace4fit_.var("rrv_number%s_%s_mj"%(label,self.channel)).getError()
                ));
        getattr(self.workspace4fit_,"import")(rrv_number_data_mj);
        scale_model_to_data=1;#rrv_number_data_mj.getVal()/rdataset_data_mj.sumEntries();
        
        if label=="_WJets0":
            mplot = rrv_mass_j.frame(RooFit.Title(""));
            rdataset_data_mj.plotOn(mplot, RooFit.Name("data_invisible"));
    
            model_data.plotOn(mplot,RooFit.Name("VV"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj,model_TTbar_%s_mj,model_VV_%s_mj"%(label,self.channel,self.channel,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn(mplot,RooFit.Name("TTbar"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj,model_TTbar_%s_mj"%(label,self.channel,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn(mplot,RooFit.Name("STop"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj"%(label,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn(mplot,RooFit.Name("WJets"), RooFit.Components("model%s_%s_mj"%(label,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
    
            model_data.plotOn(mplot,RooFit.Name("VV_invisible"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj,model_TTbar_%s_mj,model_VV_%s_mj"%(label,self.channel,self.channel,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]),RooFit.FillStyle(3003),RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn(mplot,RooFit.Name("TTbar_invisible"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj,model_TTbar_%s_mj"%(label,self.channel,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]),RooFit.FillStyle(3003),RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn(mplot,RooFit.Name("STop_invisible"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj"%(label,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]),RooFit.FillStyle(3003),RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn(mplot,RooFit.Name("WJets_invisible"), RooFit.Components("model%s_%s_mj"%(label,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]),RooFit.FillStyle(3003),RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()), RooFit.LineColor(self.color_palet["WJets"]),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
    
            #model_data.plotOn(mplot,RooFit.Name("_invisible"),RooFit.VisualizeError(rfresult,1,kFALSE),RooFit.DrawOption("F"),RooFit.FillColor(self.color_palet["Uncertainty"]),RooFit.FillStyle(3013),RooFit.LineColor(self.color_palet["Uncertainty"]),RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            #draw_error_band(rdataset_data_mj, model_data, rrv_number_data_mj,rfresult,mplot,6,"L");
            model_data.plotOn( mplot,RooFit.Name("_invisible"), RooFit.Components("model%s_%s_mj"%(label,self.channel)), RooFit.LineColor(self.color_palet["WJets"]), RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.LineStyle(kDashed) ,RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn( mplot,RooFit.Name("_invisible"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj"%(label,self.channel,self.channel)), RooFit.LineColor(self.color_palet["STop"]), RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.LineStyle(kDashed) ,RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn( mplot,RooFit.Name("_invisible"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj,model_TTbar_%s_mj"%(label,self.channel,self.channel,self.channel)), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.LineStyle(kDashed) ,RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            model_data.plotOn( mplot,RooFit.Name("_invisible"), RooFit.Components("model%s_%s_mj,model_STop_%s_mj,model_TTbar_%s_mj,model_VV_%s_mj"%(label,self.channel,self.channel,self.channel,self.channel)),RooFit.LineColor(self.color_palet["VV"]), RooFit.Range(rrv_mass_j.getMin(),rrv_mass_j.getMax()),RooFit.LineStyle(kDashed) ,RooFit.NormRange("sb_lo,sb_hi"), RooFit.VLines());
            draw_error_band(rdataset_data_mj, model_data, rrv_number_data_mj,rfresult,mplot,self.color_palet["Uncertainty"],"F");
    
            rdataset_data_mj.plotOn(mplot, RooFit.Name("data"));
    
            leg=self.legend4Plot(mplot,0);
            mplot.addObject(leg);
    
            #pull
            hpull=mplot.pullHist();
            mplot_pull = rrv_mass_j.frame(RooFit.Title("Pull Distribution"));
            mplot_pull.addPlotable(hpull,"P");
            mplot_pull.SetTitle("PULL");
            mplot_pull.GetYaxis().SetRangeUser(-5,5);
            #signal window
            lowerLine = TLine(self.mj_signal_min,0.,self.mj_signal_min,mplot.GetMaximum()); lowerLine.SetLineWidth(2); lowerLine.SetLineColor(kGray+2); lowerLine.SetLineStyle(9);
            upperLine = TLine(self.mj_signal_max,0.,self.mj_signal_max,mplot.GetMaximum()); upperLine.SetLineWidth(2); upperLine.SetLineColor(kGray+2); upperLine.SetLineStyle(9);
            mplot.addObject(lowerLine); mplot.addObject(upperLine);
            
            parameters_list=model_data.getParameters(rdataset_data_mj);
            mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1);
            self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_j_fitting_wtaggercut%s_nPV%sto%s/"%(self.channel,self.PS_model, self.wtagger_label, self.nPV_min, self.nPV_max), "m_j_sideband%s"%(label),"",1)
    
            self.get_mj_normalization_insignalregion("_data");
            self.get_mj_normalization_insignalregion("_TTbar");
            self.get_mj_normalization_insignalregion("_STop");
            self.get_mj_normalization_insignalregion("_VV");
            self.get_mj_normalization_insignalregion(label);

        # to calculate the WJets's normalization and error in M_J signal_region. The error must contain the shape error
        fullInt   = model_WJets.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j) );
        signalInt = model_WJets.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("signal_region"));
        fullInt_val=fullInt.getVal()
        signalInt_val=signalInt.getVal()/fullInt_val
        rrv_number_WJets_in_mj_signal_region_from_fitting=RooRealVar("rrv_number%s_in_mj_signal_region_from_fitting_%s"%(label,self.channel),"rrv_number%s_in_mj_signal_region_from_fitting_%s"%(label,self.channel),self.workspace4fit_.var("rrv_number%s_%s_mj"%(label,self.channel)).getVal()*signalInt_val);

        #error
        rrv_number_WJets_in_mj_signal_region_from_fitting.setError( Calc_error_extendPdf(rdataset_data_mj, model_WJets, rfresult,"signal_region") );
        print "error=%s"%(rrv_number_WJets_in_mj_signal_region_from_fitting.getError());
        getattr(self.workspace4fit_,"import")(rrv_number_WJets_in_mj_signal_region_from_fitting);
        rrv_number_WJets_in_mj_signal_region_from_fitting.Print();

   ######## ++++++++++++++
    def fit_mlvj_in_Mj_sideband(self, label, mlvj_region, mlvj_model): 
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j") 
        rrv_mass_lvj = self.workspace4fit_.var("rrv_mass_lvj") 
        rdataset_data_mlvj=self.workspace4fit_.data("rdataset_data%s_%s_mlvj"%(mlvj_region,self.channel))

        model_VV_backgrounds    = self.get_VV_mlvj_Model("_sb_lo");    number_VV_sb_lo_mlvj   =self.workspace4fit_.var("rrv_number_VV_sb_lo_%s_mlvj"%(self.channel))
        model_TTbar_backgrounds = self.get_TTbar_mlvj_Model("_sb_lo"); number_TTbar_sb_lo_mlvj=self.workspace4fit_.var("rrv_number_TTbar_sb_lo_%s_mlvj"%(self.channel))
        model_STop_backgrounds  = self.get_STop_mlvj_Model("_sb_lo");  number_STop_sb_lo_mlvj =self.workspace4fit_.var("rrv_number_STop_sb_lo_%s_mlvj"%(self.channel))

        model_pdf_WJets = self.make_Pdf("%s_sb_lo_from_fitting"%(label), mlvj_model,"_mlvj");
        model_pdf_WJets.Print();
        number_WJets_sb_lo=self.workspace4fit_.var("rrv_number%s_sb_lo_%s_mlvj"%(label,self.channel)).clone("rrv_number%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel));
        model_WJets=RooExtendPdf("model%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel),"model%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel),model_pdf_WJets,number_WJets_sb_lo);
        model_pdf_WJets.Print(); number_WJets_sb_lo.Print()

        model_data=RooAddPdf("model_data%s%s_mlvj"%(label,mlvj_region),"model_data%s%s_mlvj"%(label,mlvj_region),RooArgList(model_WJets,model_VV_backgrounds, model_TTbar_backgrounds, model_STop_backgrounds));
        rfresult = model_data.fitTo( rdataset_data_mlvj, RooFit.Save(1) ,RooFit.Extended(kTRUE) );
        rfresult = model_data.fitTo( rdataset_data_mlvj, RooFit.Save(1) ,RooFit.Extended(kTRUE) );
        rfresult.Print();
        rfresult.covarianceMatrix().Print(); #raw_input("ENTER");
        getattr(self.workspace4fit_,"import")(model_data)

        self.workspace4fit_.var("rrv_number_TTbar_sb_lo_%s_mlvj"%(self.channel)).Print();
        self.workspace4fit_.var("rrv_number_STop_sb_lo_%s_mlvj"%(self.channel)).Print();
        self.workspace4fit_.var("rrv_number_VV_sb_lo_%s_mlvj"%(self.channel)).Print();
        self.workspace4fit_.var("rrv_number%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel)).Print();
        rrv_number_data_sb_lo_mlvj=RooRealVar("rrv_number_data_sb_lo_%s_mlvj"%(self.channel),"rrv_number_data_sb_lo_%s_mlvj"%(self.channel), self.workspace4fit_.var("rrv_number_TTbar_sb_lo_%s_mlvj"%(self.channel)).getVal()+self.workspace4fit_.var("rrv_number_STop_sb_lo_%s_mlvj"%(self.channel)).getVal()+self.workspace4fit_.var("rrv_number_VV_sb_lo_%s_mlvj"%(self.channel)).getVal()+self.workspace4fit_.var("rrv_number%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel)).getVal() );
        rrv_number_data_sb_lo_mlvj.setError( TMath.Sqrt(
            self.workspace4fit_.var("rrv_number%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel)).getError()*self.workspace4fit_.var("rrv_number%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel)).getError() 
            #+self.workspace4fit_.var("rrv_number_TTbar_sb_lo_mlvj").getError()*self.workspace4fit_.var("rrv_number_TTbar_sb_lo_mlvj").getError()
            #+self.workspace4fit_.var("rrv_number_STop_sb_lo_mlvj").getError()*self.workspace4fit_.var("rrv_number_STop_sb_lo_mlvj").getError()
            #+self.workspace4fit_.var("rrv_number_VV_sb_lo_mlvj").getError()*self.workspace4fit_.var("rrv_number_VV_sb_lo_mlvj").getError() 
            ) );
        rrv_number_data_sb_lo_mlvj.setError(0.);#we only care about the M_lvj shape uncertainty
        getattr(self.workspace4fit_,"import")(rrv_number_data_sb_lo_mlvj)
        #rdataset_data_mlvj.Print(); #rrv_number_data_sb_lo_mlvj.Print();# raw_input("ENTER");
        model_WJets.Print();
        model_WJets.getParameters(rdataset_data_mlvj).Print("v");
        self.workspace4fit_.pdf("model_pdf%s_sb_lo_%s_mlvj"%(label,self.channel)).getParameters(rdataset_data_mlvj).Print("v");
        #raw_input("ENTER");

        if label=="_WJets0":
            mplot = rrv_mass_lvj.frame(RooFit.Title("M_lvj fitted in M_j sideband "));
            rdataset_data_mlvj.plotOn( mplot , RooFit.Invisible());
            model_data.plotOn(mplot, RooFit.Components("model%s_sb_lo_from_fitting_%s_mlvj,model_TTbar_sb_lo_%s_mlvj,model_STop_sb_lo_%s_mlvj,model_VV_sb_lo_%s_mlvj"%(label,self.channel,self.channel,self.channel,self.channel)), RooFit.Name("WJets"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines()) ;
            model_data.plotOn(mplot, RooFit.Components("model_TTbar_sb_lo_%s_mlvj,model_STop_sb_lo_%s_mlvj,model_VV_sb_lo_%s_mlvj"%(self.channel,self.channel,self.channel)), RooFit.Name("TTbar"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines());
            model_data.plotOn(mplot, RooFit.Components("model_STop_sb_lo_%s_mlvj,model_VV_sb_lo_%s_mlvj"%(self.channel,self.channel)), RooFit.Name("STop"), RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines());
            model_data.plotOn(mplot, RooFit.Components("model_VV_sb_lo_%s_mlvj"%(self.channel)),RooFit.Name("VV"),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines()) ;
            rdataset_data_mlvj.plotOn(mplot,RooFit.Name("data"));
            #model_data.plotOn(mplot,RooFit.VisualizeError(rfresult,1), RooFit.Name("Uncertainty"),RooFit.FillColor(self.color_palet["Uncertainty"]),RooFit.FillStyle(3013),RooFit.LineColor(self.color_palet["Uncertainty"]), RooFit.VLines(), RooFit.Invisible());#use draw_error_band to replace the roofit default algorithm
            draw_error_band(rdataset_data_mlvj, model_data,self.workspace4fit_.var("rrv_number_data_sb_lo_%s_mlvj"%(self.channel)) ,rfresult,mplot,self.color_palet["Uncertainty"],"F");
            model_data.plotOn( mplot , RooFit.VLines(), RooFit.Invisible());
            rdataset_data_mlvj.plotOn(mplot,RooFit.Name("data_invisible1"));

            leg=self.legend4Plot(mplot,0);#add legend
            mplot.addObject(leg)

            #chi2
            nPar_float_in_fitTo=rfresult.floatParsFinal().getSize();
            nBinX=mplot.GetNbinsX();
            ndof= nBinX-nPar_float_in_fitTo;
            print mplot.chiSquare();
            print "nPar=%s,  chiSquare=%s/%s"%(nPar_float_in_fitTo ,mplot.chiSquare(nPar_float_in_fitTo)*ndof, ndof ); #raw_input("ENTER");
            self.file_out.write("\n fit_mlvj_in_Mj_sideband: nPar=%s, chiSquare=%s/%s"%(nPar_float_in_fitTo, mplot.chiSquare( nPar_float_in_fitTo )*ndof, ndof ) );
    
            #pull
            hpull=mplot.pullHist();
            mplot_pull = rrv_mass_lvj.frame(RooFit.Title("Pull Distribution"));
            mplot_pull.addPlotable(hpull,"P");
            mplot_pull.SetTitle("PULL");
            mplot_pull.GetYaxis().SetRangeUser(-5,5);
    
            parameters_list=model_data.getParameters(rdataset_data_mlvj);
            mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1)
            self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_lvj_fitting/"%(self.channel,self.PS_model), "m_lvj_sb_lo%s"%(label),"",1,1)

        #model deco
        wsfit_tmp=RooWorkspace("wsfit_tmp%s_sb_lo_from_fitting_mlvj"%(label));
        Deco=PdfDiagonalizer("Deco%s_sb_lo_from_fitting_%s_mlvj"%(label,self.channel),wsfit_tmp,rfresult);
        model_pdf_WJets_deco=Deco.diagonalize(model_pdf_WJets); model_pdf_WJets_deco.Print("v");
        model_pdf_WJets_deco.getParameters(rdataset_data_mlvj).Print("") ;wsfit_tmp.allVars().Print("v");
        getattr(self.workspace4fit_,"import")(model_pdf_WJets_deco);

        self.get_WJets_mlvj_correction_sb_lo_to_signal_region(label,mlvj_model);

        self.fix_Model("_%s"%(self.higgs_sample),"_signal_region","_mlvj")
        self.fix_Model("_%s"%(self.vbfhiggs_sample),"_signal_region","_mlvj")
        self.fix_Model("_TTbar","_signal_region","_mlvj")
        self.fix_Model("_STop","_signal_region","_mlvj")
        self.fix_Model("_VV","_signal_region","_mlvj")

        self.get_mlvj_normalization_insignalregion("_%s"%(self.higgs_sample));
        self.get_mlvj_normalization_insignalregion("_%s"%(self.vbfhiggs_sample));
        self.get_mlvj_normalization_insignalregion("_TTbar");
        self.get_mlvj_normalization_insignalregion("_STop");
        self.get_mlvj_normalization_insignalregion("_VV");
        self.get_mlvj_normalization_insignalregion(label,"model_pdf%s_signal_region_%s_after_correct_mlvj"%(label,self.channel));

    ######## ++++++++++++++
    def get_mj_normalization_insignalregion(self, label):
        print "get mj normalization "+ label
        model = self.workspace4fit_.pdf("model"+label+"_"+self.channel+"_mj");
        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");

        fullInt   = model.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j) );
        sb_loInt   = model.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("sb_lo"));
        signalInt = model.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("signal_region"));
        sb_hiInt   = model.createIntegral(RooArgSet(rrv_mass_j),RooArgSet(rrv_mass_j),("sb_hi"));
        
        fullInt_val=fullInt.getVal()
        sb_loInt_val=sb_loInt.getVal()/fullInt_val
        sb_hiInt_val=sb_hiInt.getVal()/fullInt_val
        signalInt_val=signalInt.getVal()/fullInt_val

        print "Events Number in MC Dataset:"
        self.workspace4fit_.var("rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj").Print();
        self.workspace4fit_.var("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj").Print();
        self.workspace4fit_.var("rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj").Print();

        print "Events Number get from fit:"
        rrv_tmp=self.workspace4fit_.var("rrv_number"+label+"_"+self.channel+"_mj");
        rrv_tmp.Print();
        print "Events Number in sideband_low :%s"%(rrv_tmp.getVal()*sb_loInt_val)
        print "Events Number in Signal Region:%s"%(rrv_tmp.getVal()*signalInt_val)
        print "Events Number in sideband_high:%s"%(rrv_tmp.getVal()*sb_hiInt_val)
        print "Total Number in sidebands     :%s"%(rrv_tmp.getVal()*(sb_loInt_val+sb_hiInt_val)  )
        print "Ratio signal_region/sidebands        :%s"%(signalInt_val/(sb_loInt_val+sb_hiInt_val)  )

        #save to file
        self.file_out.write( "\n%s++++++++++++++++++++++++++++++++++++"%(label) )
        self.file_out.write( "\nEvents Number in sideband_low  from dataset:%s"%(self.workspace4fit_.var("rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj").getVal() ) )
        self.file_out.write( "\nEvents Number in Signal Region from dataset:%s"%(self.workspace4fit_.var("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj").getVal() ) )
        self.file_out.write( "\nEvents Number in sideband_high from dataset:%s"%(self.workspace4fit_.var("rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj").getVal() ) )
        self.file_out.write( "\nTotal  Number in sidebands     from dataset:%s"%(self.workspace4fit_.var("rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj").getVal()+ self.workspace4fit_.var("rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj").getVal() ) )
        self.file_out.write( "\nRatio signal_region/sidebands  from dataset:%s"%(self.workspace4fit_.var("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mj").getVal()/(self.workspace4fit_.var("rrv_number_dataset_sb_lo"+label+"_"+self.channel+"_mj").getVal()+ self.workspace4fit_.var("rrv_number_dataset_sb_hi"+label+"_"+self.channel+"_mj").getVal()) ) )

        self.file_out.write( "\nEvents Number in sideband_low  from fitting:%s"%(rrv_tmp.getVal()*sb_loInt_val) )
        self.file_out.write( "\nEvents Number in Signal Region from fitting:%s"%(rrv_tmp.getVal()*signalInt_val) )
        self.file_out.write( "\nEvents Number in sideband_high from fitting:%s"%(rrv_tmp.getVal()*sb_hiInt_val) )
        self.file_out.write( "\nTotal  Number in sidebands     from fitting:%s"%(rrv_tmp.getVal()*(sb_loInt_val+sb_hiInt_val)  ) )
        self.file_out.write( "\nRatio signal_region/sidebands  from fitting:%s"%(signalInt_val/(sb_loInt_val+sb_hiInt_val)  ) )

        #if label=="_WJets0": #prepare Limit of WJet Norm
        #    self.number_WJets_insideband=int(round( rrv_tmp.getVal()*(sb_loInt_val+sb_hiInt_val) ));
        #    self.datadriven_alpha_WJets_unbin =rrv_tmp.getVal()*signalInt_val/self.number_WJets_insideband

    ######## ++++++++++++++
    def get_mlvj_normalization_insignalregion(self, label, model_name=""):
        print "get mlvj normalization"
        print model_name
        if model_name=="": model = self.workspace4fit_.pdf("model"+label+"_signal_region"+"_"+self.channel+"_mlvj");
        else: model = self.workspace4fit_.pdf(model_name);

        rrv_mass_lvj = self.workspace4fit_.var("rrv_mass_lvj");

        fullInt   = model.createIntegral(RooArgSet(rrv_mass_lvj),RooArgSet(rrv_mass_lvj) );
        signalInt = model.createIntegral(RooArgSet(rrv_mass_lvj),RooArgSet(rrv_mass_lvj),("signal_region"));
        
        fullInt_val=fullInt.getVal()
        signalInt_val=signalInt.getVal()/fullInt_val

        print label+"signalInt=%s"%(signalInt_val)

        print "Events Number in MC Dataset:"
        self.workspace4fit_.var("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj").Print();
        self.workspace4fit_.var("rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj").Print();

        print "Events Number get from fit:"
        rrv_tmp=self.workspace4fit_.var("rrv_number"+label+"_signal_region"+"_"+self.channel+"_mlvj");
        rrv_tmp.Print();#raw_input("ENTER");
        print "\nEvents Number in Signal Region from fitting: %s"%(rrv_tmp.getVal()*signalInt_val)

        #save to file
        self.file_out.write( "\n%s++++++++++++++++++++++++++++++++++++"%(label) )
        self.file_out.write( "\nEvents Number in All Region from dataset   : %s"%(self.workspace4fit_.var("rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj").getVal()) )
        self.file_out.write( "\nEvents Number in Signal Region from dataset: %s"%(self.workspace4fit_.var("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj").getVal()) )
        self.file_out.write( "\nRatio signal_region/all_range from dataset  :%s"%(self.workspace4fit_.var("rrv_number_dataset_signal_region"+label+"_"+self.channel+"_mlvj").getVal()/self.workspace4fit_.var("rrv_number_dataset_AllRange"+label+"_"+self.channel+"_mlvj").getVal() ) )
        self.file_out.write( "\nEvents Number in All Region from fitting   : %s\n"%(rrv_tmp.getVal()) )
        self.file_out.write( "\nEvents Number in Signal Region from fitting: %s\n"%(rrv_tmp.getVal()*signalInt_val) )
        self.file_out.write( "\nRatio signal_region/all_range from fitting :%s"%(signalInt_val ) )

        if not self.workspace4fit_.var("rrv_number_fitting_signal_region"+label+"_"+self.channel+"_mlvj"):
            rrv_number_fitting_signal_region_mlvj=RooRealVar("rrv_number_fitting_signal_region"+label+"_"+self.channel+"_mlvj","rrv_number_fitting_signal_region"+label+"_"+self.channel+"_mlvj", rrv_tmp.getVal()*signalInt_val );
            getattr(self.workspace4fit_,"import")(rrv_number_fitting_signal_region_mlvj);
        else :
            self.workspace4fit_.var("rrv_number_fitting_signal_region"+label+"_"+self.channel+"_mlvj").setVal(rrv_tmp.getVal()*signalInt_val);
        self.workspace4fit_.var("rrv_number_fitting_signal_region"+label+"_"+self.channel+"_mlvj").Print();#raw_input("ENTER"); 
        #if label=="_WJets0" and self.number_WJets_insideband!=-1: #prepare Limit of WJet Norm
        #    self.datadriven_alpha_WJets_counting = rrv_tmp.getVal()*signalInt_val/self.number_WJets_insideband 

    ######## ++++++++++++++
    def print_limit_datacard(self, mode ,params_list=[] ): #mode:unbin or counting
        print "print_limit_datacard for %s"%(mode)
        if not (mode == "unbin" or mode == "counting"):
            print "print_limit_datacard use wrong mode: %s"%(mode);raw_input("ENTER");
        datacard_out=open(getattr(self,"file_datacard_%s"%(mode)),"w");

        datacard_out.write( "imax 1" )
        datacard_out.write( "\njmax 5" )
        datacard_out.write( "\nkmax *" )
        datacard_out.write( "\n--------------- ")
        if mode == "unbin":
            fnOnly = ntpath.basename(self.file_rlt_root)
            datacard_out.write( "\nshapes * * %s %s:$PROCESS_%s"%(fnOnly, self.workspace4limit_.GetName(), self.channel))
            datacard_out.write( "\n--------------- ")
        datacard_out.write( "\nbin 1 ")
        if mode == "unbin":
            datacard_out.write( "\nobservation %0.2f "%(self.workspace4limit_.data("data_obs_%s"%(self.channel)).sumEntries()) )
        if mode == "counting":
            datacard_out.write( "\nobservation %0.2f "%(self.workspace4limit_.var("observation_for_counting").getVal()) )
        datacard_out.write( "\n------------------------------" )
        datacard_out.write( "\nbin                1         1             1        1        1       1" )
        datacard_out.write( "\nprocess            %s    %s       WJets    TTbar    STop    VV "%(self.higgs_sample,self.vbfhiggs_sample) )
        datacard_out.write( "\nprocess            -1        0             1        2        3       4" )
        if mode == "unbin":
            datacard_out.write( "\nrate               %0.2f    %0.2f       %0.2f   %0.2f    %0.2f    %0.2f "%(self.workspace4limit_.var("rate_%s_for_unbin"%(self.higgs_sample)).getVal(),self.workspace4limit_.var("rate_%s_for_unbin"%(self.vbfhiggs_sample)).getVal(), self.workspace4limit_.var("rate_WJets_for_unbin").getVal(), self.workspace4limit_.var("rate_TTbar_for_unbin").getVal(), self.workspace4limit_.var("rate_STop_for_unbin").getVal(), self.workspace4limit_.var("rate_VV_for_unbin").getVal()  ) )
        if mode == "counting":
            datacard_out.write( "\nrate               %0.2f    %0.2f    %0.2f   %0.2f    %0.2f    %0.2f"%(self.workspace4limit_.var("rate_%s_for_counting"%(self.higgs_sample)).getVal(),self.workspace4limit_.var("rate_%s_for_counting"%(self.vbfhiggs_sample)).getVal(), self.workspace4limit_.var("rate_WJets_for_counting").getVal(), self.workspace4limit_.var("rate_TTbar_for_counting").getVal(), self.workspace4limit_.var("rate_STop_for_counting").getVal(), self.workspace4limit_.var("rate_VV_for_counting").getVal()  ) )
        datacard_out.write( "\n-------------------------------- " )
        datacard_out.write( "\nlumi     lnN       %0.3f     %0.3f         -        %0.3f   %0.3f   %0.3f"%(1.+self.lumi_uncertainty,1.+self.lumi_uncertainty,1.+self.lumi_uncertainty,1.+self.lumi_uncertainty,1.+self.lumi_uncertainty) )
        datacard_out.write( "\nQCDscale_ggH lnN   %0.3f     -             -        -       -       -"%(1.+self.QCDscale_ggH))
        datacard_out.write( "\npdf_gg       lnN   %0.3f     -             -        -       -       -"%(1.+self.pdf_gg))
        datacard_out.write( "\nhwwlnJ_pdfAcc_gg lnN %0.3f   -             -        -       -       -"%(1.+self.hwwlnJ_pdfAcc_gg) )
        datacard_out.write( "\nQCDscale_vbfH lnN  -         %0.3f         -        -       -       -"%(1.+self.QCDscale_vbfH) )
        datacard_out.write( "\npdf_qqbar     lnN  -         %0.3f         -        -       -       -"%(1.+self.pdf_vbf))
        datacard_out.write( "\nhwwlnJ_pdfAcc_vbf lnN -      %0.3f         -        -       -       -"%(1.+self.hwwlnJ_pdfAcc_vbf))
        datacard_out.write( "\nintf_ggH  lnN      %0.3f     -             -        -       -       -"%(1.+self.interference_ggH_uncertainty) )
        datacard_out.write( "\nintf_vbfH lnN      -         %0.3f         -        -       -       -"%(1.+self.interference_vbfH_uncertainty) )
        #datacard_out.write( "\nXS_TTbar lnN       -         -             -        %0.3f   -       -"%(1+self.XS_TTbar_uncertainty) )
        datacard_out.write( "\nXS_STop  lnN       -         -             -        -       %0.3f   -"%(1+self.XS_STop_uncertainty) )
        datacard_out.write( "\nXS_VV    lnN       -         -             -        -       -       %0.3f"%(1+self.XS_VV_uncertainty) )
        #print self.number_WJets_insideband; raw_input("ENTER");
        if self.number_WJets_insideband >0:
            datacard_out.write( "\nWJ_norm gmN %0.3f     -  %0.3f           -      -        -"%(self.number_WJets_insideband, getattr(self, "datadriven_alpha_WJets_%s"%(mode)) ) )
        else:
            datacard_out.write( "\nWJ_norm_%s lnN     -         -             %0.3f    -       -       -"%(self.channel, 1+ self.workspace4limit_.var("rate_WJets_for_unbin").getError()/self.workspace4limit_.var("rate_WJets_for_unbin").getVal() ) );
        datacard_out.write( "\nTop_norm_%s lnN    -         -             -        %0.3f   %0.3f   -"%(self.channel, 1+self.rrv_wtagger_eff_reweight_forTop.getError()/self.rrv_wtagger_eff_reweight_forTop.getVal(), 1+self.rrv_wtagger_eff_reweight_forTop.getError()/self.rrv_wtagger_eff_reweight_forTop.getVal() ) );
        datacard_out.write( "\nwtagger_%s lnN     %0.3f     %0.3f         -        -       -       %0.3f"%(self.channel, 1+self.rrv_wtagger_eff_reweight_forV.getError()/self.rrv_wtagger_eff_reweight_forV.getVal(), 1+self.rrv_wtagger_eff_reweight_forV.getError()/self.rrv_wtagger_eff_reweight_forV.getVal(), 1+self.rrv_wtagger_eff_reweight_forV.getError()/self.rrv_wtagger_eff_reweight_forV.getVal() ) );
        datacard_out.write( "\nbtagger_%s lnN     %0.3f     %0.3f         -        %0.3f   %0.3f   %0.3f"%(self.channel, 1+self.btag_scale_uncertainty, 1+self.btag_scale_uncertainty, 1+self.btag_scale_uncertainty, 1+self.btag_scale_uncertainty, 1+self.btag_scale_uncertainty ) );
        datacard_out.write( "\n#JetMass_%s lnN     -         -             %0.3f    %0.3f   %0.3f   %0.3f"%(self.channel, 1+self.WJets_normlization_uncertainty_from_jet_mass, 1+self.TTbar_normlization_uncertainty_from_jet_mass, 1+self.STop_normlization_uncertainty_from_jet_mass, 1+self.VV_normlization_uncertainty_from_jet_mass ) )
        datacard_out.write( "\n#trigger_%s lnN     %0.3f     %0.3f         -        %0.3f   %0.3f   %0.3f"%(self.channel, 1+self.lep_trigger_uncertainty,1+self.lep_trigger_uncertainty,1+self.lep_trigger_uncertainty,1+self.lep_trigger_uncertainty,1+self.lep_trigger_uncertainty ) );
        datacard_out.write( "\n#eff_%s   lnN       %0.3f     %0.3f         -        %0.3f   %0.3f   %0.3f"%(self.channel, 1+self.lep_eff_uncertainty,1+self.lep_eff_uncertainty,1+self.lep_eff_uncertainty,1+self.lep_eff_uncertainty,1+self.lep_eff_uncertainty ) );
        if mode == "unbin":
            for i in range(len(params_list)):
                if TString(params_list[i].GetName()).Contains("Deco_TTbar_signal_region"):
                    datacard_out.write( "\n%s param  %0.1f  %0.1f "%( params_list[i].GetName(), params_list[i].getVal(), params_list[i].getError() ) ) 
                else:
                    datacard_out.write( "\n%s param  %0.1f  %0.1f "%( params_list[i].GetName(), params_list[i].getVal(), params_list[i].getError() ) ) 
        if mode == "counting":
            datacard_out.write( "\nShape    lnN       -         -             %0.3f    -       -       -"%(1+self.rrv_counting_uncertainty_from_shape_uncertainty.getError()))
    ######## ++++++++++++++
    def prepare_limit(self,mode):
        print "prepare_limit for %s method"%(mode);
        #prepare for Limit
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_mass_lvj"));
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_fitting_signal_region_%s_%s_mlvj"%(self.higgs_sample,self.channel)).clone("rate_%s_for_counting"%(self.higgs_sample) ) )
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_fitting_signal_region_%s_%s_mlvj"%(self.vbfhiggs_sample,self.channel)).clone("rate_%s_for_counting"%(self.vbfhiggs_sample) ) )
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_fitting_signal_region_WJets0_%s_mlvj"%(self.channel)).clone("rate_WJets_for_counting"))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_fitting_signal_region_VV_%s_mlvj"%(self.channel)).clone("rate_VV_for_counting"))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_fitting_signal_region_TTbar_%s_mlvj"%(self.channel)).clone("rate_TTbar_for_counting"))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_fitting_signal_region_STop_%s_mlvj"%(self.channel)).clone("rate_STop_for_counting"))

        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_%s_signal_region_%s_mlvj"%(self.higgs_sample, self.channel)).clone("rate_%s_for_unbin"%(self.higgs_sample)));
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_%s_signal_region_%s_mlvj"%(self.vbfhiggs_sample, self.channel)).clone("rate_%s_for_unbin"%(self.vbfhiggs_sample)));
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_WJets0_signal_region_%s_mlvj"%(self.channel)).clone("rate_WJets_for_unbin"));
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_VV_signal_region_%s_mlvj"%(self.channel)).clone("rate_VV_for_unbin"));
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_TTbar_signal_region_%s_mlvj"%(self.channel)).clone("rate_TTbar_for_unbin"));
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_STop_signal_region_%s_mlvj"%(self.channel)).clone("rate_STop_for_unbin"));
        self.workspace4limit_.var("rate_VV_for_unbin").setError(self.workspace4limit_.var("rate_VV_for_unbin").getVal()*TMath.Sqrt( self.lumi_uncertainty*self.lumi_uncertainty  + self.rrv_wtagger_eff_reweight_forV.getError()/self.rrv_wtagger_eff_reweight_forV.getVal()*self.rrv_wtagger_eff_reweight_forV.getError()/self.rrv_wtagger_eff_reweight_forV.getVal() +self.XS_VV_uncertainty*self.XS_VV_uncertainty )    );
        self.workspace4limit_.var("rate_STop_for_unbin").setError(self.workspace4limit_.var("rate_STop_for_unbin").getVal()*TMath.Sqrt( self.lumi_uncertainty*self.lumi_uncertainty  + self.rrv_wtagger_eff_reweight_forTop.getError()/self.rrv_wtagger_eff_reweight_forTop.getVal()*self.rrv_wtagger_eff_reweight_forTop.getError()/self.rrv_wtagger_eff_reweight_forTop.getVal() +self.XS_STop_uncertainty*self.XS_STop_uncertainty )    );
        self.workspace4limit_.var("rate_TTbar_for_unbin").setError(self.workspace4limit_.var("rate_TTbar_for_unbin").getVal()*TMath.Sqrt( self.lumi_uncertainty*self.lumi_uncertainty  + self.rrv_wtagger_eff_reweight_forTop.getError()/self.rrv_wtagger_eff_reweight_forTop.getVal()*self.rrv_wtagger_eff_reweight_forTop.getError()/self.rrv_wtagger_eff_reweight_forTop.getVal() )) #+self.XS_TTbar_uncertainty*self.XS_TTbar_uncertainty )    );
 
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.data("rdataset_data_signal_region_%s_mlvj"%(self.channel)).Clone("data_obs_%s"%(self.channel)))
        if mode=="sideband_correction_method1":
            getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_WJets0_signal_region_%s_after_correct_mlvj"%(self.channel)).clone("WJets_%s"%(self.channel)))
            self.workspace4limit_.allVars().Print();
        #getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_TTbar_signal_region_%s_mlvj"%(self.channel)).clone("TTbar_%s"%(self.channel)))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_TTbar_signal_region_%s_mlvj_Deco_TTbar_signal_region_%s_mlvj"%(self.channel, self.channel)).clone("TTbar_%s"%(self.channel)))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_STop_signal_region_%s_mlvj"%(self.channel)).clone("STop_%s"%(self.channel)))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_VV_signal_region_%s_mlvj"%(self.channel)).clone("VV_%s"%(self.channel)))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_%s_signal_region_%s_mlvj"%(self.higgs_sample,self.channel)).clone(self.higgs_sample+"_%s"%(self.channel)))
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.pdf("model_pdf_%s_signal_region_%s_mlvj"%(self.vbfhiggs_sample,self.channel)).clone(self.vbfhiggs_sample+"_%s"%(self.channel)))

        rrv_x=self.workspace4limit_.var("rrv_mass_lvj");
        self.fix_Pdf(self.workspace4limit_.pdf("TTbar_%s"%(self.channel)), RooArgSet(rrv_x) ); 
        self.fix_Pdf(self.workspace4limit_.pdf("STop_%s"%(self.channel)), RooArgSet(rrv_x)); 
        self.fix_Pdf(self.workspace4limit_.pdf("VV_%s"%(self.channel)), RooArgSet(rrv_x)); 
        self.fix_Pdf(self.workspace4limit_.pdf("WJets_%s"%(self.channel)), RooArgSet(rrv_x)); 

        params_list=[];
        shape_para_error_WJets0=1.4;# for sb_lo fitting
        shape_para_error_alpha=1.4;#for alpha
        if self.higgs_sample=="ggH600" or self.higgs_sample=="ggH700":shape_para_error_alpha=1.4;
        else: shape_para_error_alpha=2.;

        shape_para_error_TTbar=2.;
  
        if mode=="sideband_correction_method1":
            if self.MODEL_4_mlvj=="ErfExp_v1" or self.MODEL_4_mlvj=="ErfPow_v1" :
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig3"%(self.channel)).setError(shape_para_error_WJets0);
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig3"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig3"%(self.channel)) ); 

                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig4"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig4"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig5"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig5"%(self.channel)))
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig4"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig5"%(self.channel)) ); 

                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_TTbar);
                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_TTbar);
                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_TTbar);
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig2"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig2"%(self.channel))); 

            if self.MODEL_4_mlvj=="ErfPow2_v1" or self.MODEL_4_mlvj=="ErfPowExp_v1" :
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig3"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig4"%(self.channel)).setError(shape_para_error_WJets0);
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig3"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig4"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig3"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig4"%(self.channel)) ); 
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig4"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig4"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig5"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig5"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig6"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig6"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig7"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig7"%(self.channel)))
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig4"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig5"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig6"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig7"%(self.channel)) ); 

                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_TTbar);
                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_TTbar);
                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_TTbar);
                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig3"%(self.channel)).setError(shape_para_error_TTbar);
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig2"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig3"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig2"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig3"%(self.channel))); 

            if self.MODEL_4_mlvj=="Exp" or self.MODEL_4_mlvj=="Pow" :
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_WJets0);
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)) ); 
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)))
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)) ); 

                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_TTbar);
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel))); 
            if self.MODEL_4_mlvj=="Pow2" :
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_WJets0);
                self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_WJets0);
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)));
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig1"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sb_lo_from_fitting_%s_mlvj_eig2"%(self.channel)) ); 
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)))
                self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)).setError(shape_para_error_alpha); params_list.append(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)))
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig0"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig1"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig2"%(self.channel)) ); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_WJets0_sim_%s_mlvj_eig3"%(self.channel)) ); 

                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)).setError(shape_para_error_TTbar); 
                self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel)).setError(shape_para_error_TTbar);
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel)));
                params_list.append(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig0"%(self.channel))); 
                self.FloatingParams.add(self.workspace4limit_.var("Deco_TTbar_signal_region_%s_mlvj_eig1"%(self.channel))); 

        getattr(self.workspace4limit_,"import")(self.FloatingParams);
 
        self.save_workspace_to_file();
        #calculate the shape uncertainty for cut-and-countingd
        self.rrv_counting_uncertainty_from_shape_uncertainty=RooRealVar("rrv_counting_uncertainty_from_shape_uncertainty_%s"%(self.channel),"rrv_counting_uncertainty_from_shape_uncertainty_%s"%(self.channel),0);
        self.rrv_counting_uncertainty_from_shape_uncertainty.setError( Calc_error("WJets_%s"%(self.channel), "rrv_mass_lvj" ,self.FloatingParams,self.workspace4limit_,"signal_region") );
        self.rrv_counting_uncertainty_from_shape_uncertainty.Print();

        self.print_limit_datacard("unbin",params_list);
        self.print_limit_datacard("counting");

    ######### ++++++++++++++
    def read_workspace(self):
        file = TFile(self.file_rlt_root) ;
        workspace = file.Get("workspace4limit_") ;
        workspace.Print()

        parameters_workspace=workspace.allVars();
        par=parameters_workspace.createIterator();
        par.Reset();
        param=par.Next()
        while (param):
            param.Print();
            param=par.Next()
        print "___________________________________________________"

        workspace.data("data_obs_%s"%(self.channel)).Print()
        print "___________________________________________________"
        pdfs_workspace=workspace.allPdfs();
        par=pdfs_workspace.createIterator();
        par.Reset();
        param=par.Next()
        while (param):
            param.Print();
            param=par.Next()
        print "___________________________________________________"

        rrv_x=workspace.var("rrv_mass_lvj")
        data_obs=workspace.data("data_obs_%s"%(self.channel))
        model_pdf_ggH=workspace.pdf("%s_%s"%(self.higgs_sample,self.channel))
        model_pdf_vbfH=workspace.pdf("%s_%s"%(self.vbfhiggs_sample,self.channel))
        model_pdf_WJets=workspace.pdf("WJets_%s"%(self.channel))
        model_pdf_VV=workspace.pdf("VV_%s"%(self.channel))
        model_pdf_TTbar=workspace.pdf("TTbar_%s"%(self.channel))
        model_pdf_STop=workspace.pdf("STop_%s"%(self.channel))

        model_pdf_ggH.Print();
        model_pdf_vbfH.Print();
        model_pdf_WJets.Print();
        model_pdf_VV.Print();
        model_pdf_TTbar.Print();
        model_pdf_STop.Print();

        rrv_number_ggH=workspace.var("rate_%s_for_unbin"%(self.higgs_sample))
        rrv_number_vbfH=workspace.var("rate_%s_for_unbin"%(self.vbfhiggs_sample))
        rrv_number_WJets=workspace.var("rate_WJets_for_unbin")
        rrv_number_VV=workspace.var("rate_VV_for_unbin")
        rrv_number_TTbar=workspace.var("rate_TTbar_for_unbin")
        rrv_number_STop=workspace.var("rate_STop_for_unbin")

        rrv_number_ggH.Print();
        rrv_number_vbfH.Print();
        rrv_number_WJets.Print();
        rrv_number_VV.Print();
        rrv_number_TTbar.Print();
        rrv_number_STop.Print();

        rrv_number_Total_background_MC = RooRealVar("rrv_number_Total_background_MC","rrv_number_Total_background_MC",
                rrv_number_WJets.getVal()+
                rrv_number_VV.getVal()+
                rrv_number_TTbar.getVal()+
                rrv_number_STop.getVal());
        rrv_number_Total_background_MC.setError(TMath.Sqrt(
                rrv_number_WJets.getError()* rrv_number_WJets.getError()+
                rrv_number_VV.getError()* rrv_number_VV.getError()+
                rrv_number_TTbar.getError()* rrv_number_TTbar.getError()+
                rrv_number_STop.getError() *rrv_number_STop.getError() 
                ));
        #rrv_number_Total_background_MC.setError(0.);#we are not only care about the shape uncertainty, but also the rate uncertainty
        model_Total_background_MC = RooAddPdf("model_Total_background_MC","model_Total_background_MC",RooArgList(model_pdf_WJets,model_pdf_VV,model_pdf_TTbar,model_pdf_STop),RooArgList(rrv_number_WJets,rrv_number_VV,rrv_number_TTbar,rrv_number_STop));

        scale_number_ggH=rrv_number_ggH.getVal()/data_obs.sumEntries()
        scale_number_vbfH=rrv_number_vbfH.getVal()/data_obs.sumEntries()
        scale_number_Total_background_MC=rrv_number_Total_background_MC.getVal()/data_obs.sumEntries()

        mplot=rrv_x.frame(RooFit.Title("check_workspace"));
        #data_obs.plotOn(mplot ,RooFit.DataError(RooAbsData.SumW2), RooFit.Name("data_invisible"),RooFit.Invisible());
        data_obs.plotOn(mplot , RooFit.Name("data_invisible"));

        model_Total_background_MC.plotOn(mplot,RooFit.Normalization(scale_number_Total_background_MC),RooFit.Name("WJets"), RooFit.Components("WJets_%s,VV_%s,TTbar_%s,STop_%s"%(self.channel,self.channel,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["WJets"]), RooFit.LineColor(self.color_palet["WJets"]), RooFit.VLines());
        model_Total_background_MC.plotOn(mplot,RooFit.Normalization(scale_number_Total_background_MC),RooFit.Name("VV"), RooFit.Components("VV_%s,TTbar_%s,STop_%s"%(self.channel,self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["VV"]), RooFit.LineColor(self.color_palet["VV"]), RooFit.VLines());
        model_Total_background_MC.plotOn(mplot,RooFit.Normalization(scale_number_Total_background_MC),RooFit.Name("TTbar"), RooFit.Components("TTbar_%s,STop_%s"%(self.channel,self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["TTbar"]), RooFit.LineColor(self.color_palet["TTbar"]), RooFit.VLines());
        model_Total_background_MC.plotOn(mplot,RooFit.Normalization(scale_number_Total_background_MC),RooFit.Name("STop"), RooFit.Components("STop_%s"%(self.channel)),RooFit.DrawOption("F"), RooFit.FillColor(self.color_palet["STop"]), RooFit.LineColor(self.color_palet["STop"]), RooFit.VLines());
        if self.higgs_sample=="ggH600" or self.higgs_sample=="ggH700":
            signal_scale=5;
        else: signal_scale=10;
        model_pdf_ggH.plotOn(mplot,RooFit.Normalization(scale_number_ggH*signal_scale),RooFit.Name("%s #times %s"%(self.higgs_sample, signal_scale)),RooFit.DrawOption("L"), RooFit.LineColor(self.color_palet["Signal"]), RooFit.VLines());
        model_pdf_vbfH.plotOn(mplot,RooFit.Normalization(scale_number_vbfH*signal_scale),RooFit.Name("%s #times %s"%(self.vbfhiggs_sample,signal_scale)),RooFit.DrawOption("L"), RooFit.LineColor(self.color_palet["vbfSignal"]), RooFit.VLines());
        data_obs.plotOn(mplot, RooFit.Name("data"));
        model_Total_background_MC.plotOn(mplot,RooFit.Normalization(scale_number_Total_background_MC),RooFit.Invisible());
        hpull=mplot.pullHist();
        
        #floatpara_list=workspace.FindObject("floatpara_list");
        self.FloatingParams.Print("v");
        draw_error_band(model_Total_background_MC, rrv_x.GetName(), rrv_number_Total_background_MC,self.FloatingParams,workspace ,mplot,self.color_palet["Uncertainty"],"F");

        mplot.Print();
        leg=self.legend4Plot(mplot,0);
        mplot.addObject(leg);
        mplot.GetYaxis().SetRangeUser(1e-2,mplot.GetMaximum()*1.1);

        mplot_pull = rrv_x.frame(RooFit.Title("Pull Distribution"));
        mplot_pull.addPlotable(hpull,"P");
        mplot_pull.SetTitle("PULL");
        parameters_list=RooArgList();
        self.draw_canvas( mplot, mplot_pull,parameters_list,"plots_%s_%s/m_lvj_fitting/"%(self.channel,self.PS_model),"check_workspace_for_limit","",0,1);
        if workspace.var("rrv_num_floatparameter_in_last_fitting"):   nPar_float_in_fitTo= int(workspace.var("rrv_num_floatparameter_in_last_fitting").getVal());
        else:
            nPar_float_in_fitTo=1;
        nBinX=mplot.GetNbinsX();
        ndof= nBinX-nPar_float_in_fitTo; 
        print "nPar=%s, chiSquare=%s/%s"%(nPar_float_in_fitTo, mplot.chiSquare( nPar_float_in_fitTo )*ndof, ndof );

    ######## ++++++++++++++
    def save_workspace_to_file(self):
        self.workspace4limit_.writeToFile(self.file_rlt_root);
        self.file_out.close()

    ######## ++++++++++++++
    def legend4Plot(self, plot, left=1):
        if left: 
            theLeg = TLegend(0.2, 0.62, 0.55, 0.92, "", "NDC");
        else:
            theLeg = TLegend(0.65, 0.57, 0.92, 0.87, "", "NDC");
        theLeg.SetName("theLegend");
        theLeg.SetBorderSize(0);
        theLeg.SetLineColor(0);
        theLeg.SetFillColor(0);
        theLeg.SetFillStyle(0);
        theLeg.SetLineWidth(0);
        theLeg.SetLineStyle(0);
        theLeg.SetTextFont(42);
        theLeg.SetTextSize(.04);
        #theLeg.SetTextSize(.045);
        
        entryCnt = 0;
        objName_before = "";
        for obj in range(int(plot.numItems()) ):
            objName = plot.nameOf(obj);
            print objName;
            if not ( ( (plot.getInvisible(objName)) and (not TString(objName).Contains("Uncertainty")) ) or TString(objName).Contains("invisi") or objName==objName_before  ): 
                theObj = plot.getObject(obj);
                objTitle = objName;
                drawoption= plot.getDrawOptions(objName).Data()
                if drawoption=="P":drawoption="PE"
                #if TString(objName).Contains("Graph") or TString(objName).Contains("Uncertainty"): theLeg.AddEntry(theObj, "Uncertainty","F");
                if TString(objName).Contains("Uncertainty") or TString(objName).Contains("sigma"): 
                    theLeg.AddEntry(theObj, objName,"F");
                elif TString(objName).Contains("Graph") :
                    if  not (objName_before=="Graph" or objName_before=="Uncertainty"): theLeg.AddEntry(theObj, "Uncertainty","F");
                else: 
                    if TString(objName).Contains("STop"): theLeg.AddEntry(theObj, "Single-Top","F");
                    else : theLeg.AddEntry(theObj, objTitle,drawoption);
                entryCnt=entryCnt+1;
            objName_before=objName;

        theLeg.SetY1NDC(0.9 - 0.05*entryCnt - 0.005);
        theLeg.SetY1(theLeg.GetY1NDC());
        return theLeg;

    ######## ++++++++++++++
    def draw_canvas(self, mplot, mplot_pull,parameters_list,in_directory, in_file_name, in_model_name="", show_constant_parameter=0, log=0):# mplot + pull + parameters

        mplot.GetXaxis().SetTitleOffset(1.1);
        mplot.GetYaxis().SetTitleOffset(1.1);
        mplot.GetXaxis().SetTitleSize(0.04);
        mplot.GetYaxis().SetTitleSize(0.04);
        mplot.GetXaxis().SetLabelSize(0.04);
        mplot.GetYaxis().SetLabelSize(0.04);
        #mplot_pull.GetYaxis().SetTitleOffset(0.50);
    	mplot_pull.GetXaxis().SetLabelSize(0.09);
    	mplot_pull.GetYaxis().SetLabelSize(0.13);
    	mplot_pull.GetYaxis().SetNdivisions(205);

        mplot_pull.GetYaxis().SetTitle("PULL");
        mplot_pull.GetYaxis().SetTitleOffset(0.50);
        mplot_pull.GetYaxis().SetTitleSize(0.08);
        mplot_pull.GetYaxis().SetRangeUser(-5,5);
        cMassFit = TCanvas("cMassFit","cMassFit",1000,800);
        # if parameters_list is empty, don't draw pad3
        par_first=parameters_list.createIterator();
        par_first.Reset();
        param_first=par_first.Next()
        if param_first:
            pad1=TPad("pad1","pad1",0.,0. ,0.8,0.2);
            pad2=TPad("pad2","pad2",0.,0.2,0.8,1. );
            pad3=TPad("pad3","pad3",0.8,0.,1,1);
            pad1.Draw();
            pad2.Draw();
            pad3.Draw();
        else:
            pad1=TPad("pad1","pad1",0.1,0. ,0.9,0.2);
            pad2=TPad("pad2","pad2",0.1,0.2,0.9,1. );
            pad1.Draw();
            pad2.Draw();

        pad2.cd();
        mplot.Draw();
        banner = TLatex(0.18,0.96,("CMS Preliminary, %.1f fb^{-1} at #sqrt{s}=8TeV %s+jets"%(self.GetLumi(),self.channel)));
        banner.SetNDC(); banner.SetTextSize(0.028);
        banner.Draw();

        pad1.cd();
        mplot_pull.Draw();

        if param_first:
            pad3.cd();
            latex=TLatex();
            latex.SetTextSize(0.1);
            par=parameters_list.createIterator();
            par.Reset();
            param=par.Next()
            i=0;
            while param:
                if (not  param.isConstant() ) or show_constant_parameter:
                    param.Print();
                    icolor=1;#if a paramenter is constant, color is 2
                    if param.isConstant(): icolor=2
                    latex.DrawLatex(0,0.9-i*0.04,"#color[%s]{%s}"%(icolor,param.GetName()) );
                    latex.DrawLatex(0,0.9-i*0.04-0.02," #color[%s]{%4.3e +/- %2.1e}"%(icolor,param.getVal(),param.getError()) );
                    i=i+1;
                param=par.Next();


        Directory=TString(in_directory+self.higgs_sample+"_%02d_%02d/"%(options.cprime,options.BRnew));
        if not Directory.EndsWith("/"):Directory=Directory.Append("/");
        if not os.path.isdir(Directory.Data()): os.system("mkdir -p  "+Directory.Data());

        rlt_file=TString(Directory.Data()+in_file_name);
        if rlt_file.EndsWith(".root"):
            rlt_file.ReplaceAll(".root","_"+in_model_name+"_rlt.png");
        else:
            rlt_file=rlt_file.Append("_"+in_model_name+"_rlt.png");
        cMassFit.SaveAs(rlt_file.Data());
        rlt_file.ReplaceAll(".png",".eps"); 
        cMassFit.SaveAs(rlt_file.Data());

        string_file_name=TString(in_file_name);
        if string_file_name.EndsWith(".root"): string_file_name.ReplaceAll(".root",in_model_name);
        else: rlt_file.Append(in_model_name);
        self.draw_canvas1(mplot,in_directory,string_file_name.Data(),0,log);

    ######## ++++++++++++++
    def draw_canvas_MCscale(self, mplot, mplot_addition,in_directory, in_file_name, in_model_name="", show_constant_parameter=0, log=0):#mplot + MC/data scale

        mplot.GetXaxis().SetTitleOffset(1.1);
        mplot.GetYaxis().SetTitleOffset(1.1);
        mplot.GetXaxis().SetTitleSize(0.04);
        mplot.GetYaxis().SetTitleSize(0.04);
        mplot.GetXaxis().SetLabelSize(0.04);
        mplot.GetYaxis().SetLabelSize(0.04);
        mplot_addition.GetYaxis().SetTitleOffset(1.0);

        cMassFit = TCanvas("cMassFit","cMassFit",1000,800);
        pad1=TPad("pad1","pad1",0.00,0.25,1.00,0.97);
        pad2=TPad("pad2","pad2",0.00,0.00,1.00,0.25);
        pad1.Draw();
        pad2.Draw();

        pad1.cd();
        mplot.Draw();
        banner = TLatex(0.18,0.96,("CMS Preliminary, %.1f fb^{-1} at #sqrt{s}=8TeV %s+jets"%(self.GetLumi(),self.channel)));
        banner.SetNDC(); banner.SetTextSize(0.028);
        banner.Draw();

        pad2.cd();
        mplot_addition.Draw();

        Directory=TString(in_directory+self.higgs_sample+"_%02d_%02d/"%(options.cprime,options.BRnew));
        if not Directory.EndsWith("/"):Directory=Directory.Append("/");
        if not os.path.isdir(Directory.Data()): os.system("mkdir -p  "+Directory.Data());

        rlt_file=TString(Directory.Data()+in_file_name);
        if rlt_file.EndsWith(".root"):
            rlt_file.ReplaceAll(".root","_"+in_model_name+"_rlt.png");
        else:
            rlt_file=rlt_file.Append("_"+in_model_name+"_rlt.png");
        cMassFit.SaveAs(rlt_file.Data());
        rlt_file.ReplaceAll(".png",".eps"); 
        cMassFit.SaveAs(rlt_file.Data());

        string_file_name=TString(in_file_name);
        if string_file_name.EndsWith(".root"): string_file_name.ReplaceAll(".root",in_model_name);
        else: rlt_file.Append(in_model_name);
        self.draw_canvas1(mplot,in_directory,string_file_name.Data(),0,log);
        
    ######## ++++++++++++++
    def draw_canvas1(self, in_obj,in_directory, in_file_name, is_range=0, log=0):
        cMassFit = TCanvas("cMassFit","cMassFit",1000,800);
        if is_range:
            h2=TH2D("h2","",100,400,1400,4,0.00001,4); h2.Draw(); in_obj.Draw("same")
        else : 
            in_obj.Draw()

        in_obj.GetXaxis().SetTitleOffset(1.1);
        in_obj.GetYaxis().SetTitleOffset(1.1);
        in_obj.GetXaxis().SetTitleSize(0.04);
        in_obj.GetYaxis().SetTitleSize(0.04);
        in_obj.GetXaxis().SetLabelSize(0.04);
        in_obj.GetYaxis().SetLabelSize(0.04);

        banner = TLatex(0.18,0.96,("CMS Preliminary, %.1f fb^{-1} at #sqrt{s}=8TeV %s+jets"%(self.GetLumi(),self.channel)));
        banner.SetNDC(); banner.SetTextSize(0.028);
        banner.Draw();

        Directory=TString(in_directory+self.higgs_sample+"_%02d_%02d/"%(options.cprime,options.BRnew));
        if not Directory.EndsWith("/"):Directory=Directory.Append("/");
        if not os.path.isdir(Directory.Data()): os.system("mkdir -p  "+Directory.Data());

        rlt_file=TString(Directory.Data()+in_file_name);
        if rlt_file.EndsWith(".root"):
            rlt_file.ReplaceAll(".root","_rlt_without_pull_and_paramters.png");
        else:
            #rlt_file=rlt_file.Append("_rlt_without_pull_and_paramters.png");
            rlt_file=rlt_file.Append(".png");
        cMassFit.SaveAs(rlt_file.Data());
        rlt_file.ReplaceAll(".png",".eps"); 
        cMassFit.SaveAs(rlt_file.Data());

        if log:
            cMassFit.SetLogy() ;
            cMassFit.Update();
            rlt_file.ReplaceAll(".eps","_log.eps"); 
            cMassFit.SaveAs(rlt_file.Data());
            rlt_file.ReplaceAll(".eps",".png"); 
            cMassFit.SaveAs(rlt_file.Data());

    ######## ++++++++++++++
    def GetLumi(self):
        if options.fitwtagger or options.fitwtaggersim:
            if self.channel=="el": return 19.2#13.9;
            if self.channel=="mu": return 19.3#14.0;

        if self.channel=="el": return 19.2#5.1#19.2#13.9;
        if self.channel=="mu": return 19.3#5.3#19.3#14.0;


    ######## ++++++++++++++
    def get_data(self):
        print "get_data"
        self.get_mj_and_mlvj_dataset(self.file_data,"_data")
        self.get_mj_and_mlvj_dataset(self.file_data,"_data")
        self.get_mj_and_mlvj_dataset(self.file_data,"_datamassup","jet_mass_pr_up")
        self.get_mj_and_mlvj_dataset(self.file_data,"_datamassdn","jet_mass_pr_dn")
        getattr(self.workspace4limit_,"import")(self.workspace4fit_.var("rrv_number_dataset_signal_region_data_%s_mlvj"%(self.channel)).clone("observation_for_counting"))
 
    ######## ++++++++++++++
    def fit_Signal(self):
        print "fit_Signal"
        self.get_mj_and_mlvj_dataset(self.file_ggH,"_%s"%(self.higgs_sample))# to get the shape of m_lvj
        self.fit_mj_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"Voig");

        # for VBF sample
        self.get_mj_and_mlvj_dataset(self.file_vbfH,"_%s"%(self.vbfhiggs_sample))# to get the shape of m_lvj
        self.fit_mj_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"Voig");

        if self.higgs_sample=="ggH600":
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","CB_v1");
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","CB_v1");
            self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","CB_v1"); 
        elif self.higgs_sample=="ggH700":
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","Voig_v1");
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","CB_v1");
            self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","CB_v1"); 
        elif self.higgs_sample=="ggH800":
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","Voig_v1");
            #self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","Voig_v1");
            #self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","Voig_v1"); 
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","CB_v1");
            self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","CB_v1"); 
        elif self.higgs_sample=="ggH900":
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","Voig_v1");
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","CB_v1"); 
            self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","CB_v1"); 
        elif self.higgs_sample=="ggH1000":
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","BW_v1");
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","CB_v1");  
            self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","CB_v1"); 
            #self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","ArgusBW_v1");  
            #self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","ArgusBW_v1"); 
        else:
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","BW_v1");
            self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","BW_v1");  
            self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","BW_v1"); 
        #self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","CB_v1");
        #self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","CB_v1");  
        #self.fit_mlvj_model_single_MC(self.file_vbfH,"_%s"%(self.vbfhiggs_sample),"_signal_region","CB_v1"); 
        print "________________________________________________________________________"


    ######## ++++++++++++++
    def fit_Signal_new(self):
        print "fit_Signal_new"
        self.get_mj_and_mlvj_dataset(self.file_ggH,"_%s"%(self.higgs_sample))# to get the shape of m_lvj
        #self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_sb_lo","CB_v1");
        self.fit_mlvj_model_single_MC(self.file_ggH,"_%s"%(self.higgs_sample),"_signal_region","BWRUN");
 
    ######## ++++++++++++++
    def fit_WJets(self):
        print "fit_WJets"
        self.get_mj_and_mlvj_dataset(self.file_WJets0_mc,"_WJets0")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_WJets1_mc,"_WJets1")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_WJets0_mc,"_WJets01")# to get the shape of m_lvj
        #jet mass down and up
        self.get_mj_and_mlvj_dataset(self.file_WJets0_mc,"_WJets0massup","jet_mass_pr_up")
        self.get_mj_and_mlvj_dataset(self.file_WJets0_mc,"_WJets0massdn","jet_mass_pr_dn")
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0","User1");
        self.fit_mj_single_MC(self.file_WJets1_mc,"_WJets1","User1");# use for estimating the PS model uncertainty
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets01","ErfExp");# use for estimating the fitting model uncertainty
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0massup","User1");
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0massdn","User1");
        self.fit_mlvj_model_single_MC(self.file_WJets0_mc,"_WJets0","_sb_lo",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_WJets0_mc,"_WJets0","_signal_region",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_WJets1_mc,"_WJets1","_sb_lo",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_WJets1_mc,"_WJets1","_signal_region",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_WJets0_mc,"_WJets01","_sb_lo",self.MODEL_4_mlvj_alter);
        self.fit_mlvj_model_single_MC(self.file_WJets0_mc,"_WJets01","_signal_region",self.MODEL_4_mlvj_alter);
        print "________________________________________________________________________"

    ######## ++++++++++++++
    def fit_VV(self):
        print "fit_VV"
        self.get_mj_and_mlvj_dataset(self.file_VV_mc,"_VV")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_VV_mc,"_VVmassup","jet_mass_pr_up")
        self.get_mj_and_mlvj_dataset(self.file_VV_mc,"_VVmassdn","jet_mass_pr_dn")
        self.fit_mj_single_MC(self.file_VV_mc,"_VV","2Voig");
        self.fit_mj_single_MC(self.file_VV_mc,"_VVmassup","2Voig");
        self.fit_mj_single_MC(self.file_VV_mc,"_VVmassdn","2Voig");
        #self.fit_mlvj_model_single_MC(self.file_VV_mc,"_VV","_sb_lo","ErfPowExp_v1");
        #self.fit_mlvj_model_single_MC(self.file_VV_mc,"_VV","_signal_region","ErfPowExp_v1");
        if self.MODEL_4_mlvj=="ErfPowExp_v1":
            self.fit_mlvj_model_single_MC(self.file_VV_mc,"_VV","_sb_lo","ErfExp_v1");
        else:
            self.fit_mlvj_model_single_MC(self.file_VV_mc,"_VV","_sb_lo",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_VV_mc,"_VV","_signal_region",self.MODEL_4_mlvj);
 
        print "________________________________________________________________________"

    ######## ++++++++++++++
    def fit_TTbar(self):
        print "fit_TTbar"
        self.get_mj_and_mlvj_dataset(self.file_TTbar_mc,"_TTbar")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_TTbar_matchDn_mc,"_TTbar_matchDn")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_TTbar_matchUp_mc,"_TTbar_matchUp")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_TTbar_scaleDn_mc,"_TTbar_scaleDn")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_TTbar_scaleUp_mc,"_TTbar_scaleUp")# to get the shape of m_lvj
        #self.get_mj_and_mlvj_dataset(self.file_TTbar_Powheg_mc,"_TTbar_Powheg")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_TTbar_MG_mc,"_TTbar_MG")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_TTbar_mc,"_TTbarmassup","jet_mass_pr_up")
        self.get_mj_and_mlvj_dataset(self.file_TTbar_mc,"_TTbarmassdn","jet_mass_pr_dn")
        self.fit_mj_single_MC(self.file_TTbar_mc,"_TTbar","ErfExpGaus_sp");
        self.fit_mj_single_MC(self.file_TTbar_mc,"_TTbarmassup","ErfExpGaus_sp");
        self.fit_mj_single_MC(self.file_TTbar_mc,"_TTbarmassdn","ErfExpGaus_sp");
        #self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_sb_lo","ErfPowExp_v1");
        #self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_signal_region","ErfPowExp_v1");
        #self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_sb_lo",self.MODEL_4_mlvj);
        if self.MODEL_4_mlvj=="ErfPowExp_v1":
            self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_sb_lo","ErfExp_v1");
            self.fit_mlvj_model_single_MC(self.file_TTbar_matchDn_mc,"_TTbar_matchDn","_signal_region","ErfExp_v1");
        else:
            self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_sb_lo",self.MODEL_4_mlvj);
            self.fit_mlvj_model_single_MC(self.file_TTbar_matchDn_mc,"_TTbar_matchDn","_signal_region",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_TTbar_matchUp_mc,"_TTbar_matchUp","_signal_region",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_TTbar_scaleDn_mc,"_TTbar_scaleDn","_signal_region",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_TTbar_scaleUp_mc,"_TTbar_scaleUp","_signal_region",self.MODEL_4_mlvj);
        #self.fit_mlvj_model_single_MC(self.file_TTbar_Powheg_mc,"_TTbar_Powheg","_signal_region",self.MODEL_4_mlvj);
        self.fit_mlvj_model_single_MC(self.file_TTbar_MG_mc,"_TTbar_MG","_signal_region",self.MODEL_4_mlvj);
        if self.MODEL_4_mlvj=="ErfPowExp_v1" and self.mj_signal_min==65:
            self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_signal_region","ErfPowExp_v1_0",1);
        else:
            self.fit_mlvj_model_single_MC(self.file_TTbar_mc,"_TTbar","_signal_region",self.MODEL_4_mlvj,1);
 
        print "________________________________________________________________________"


    ######## ++++++++++++++
    def fit_STop(self):
        print "fit_STop"
        self.get_mj_and_mlvj_dataset(self.file_STop_mc,"_STop")# to get the shape of m_lvj
        self.get_mj_and_mlvj_dataset(self.file_STop_mc,"_STopmassup","jet_mass_pr_up")
        self.get_mj_and_mlvj_dataset(self.file_STop_mc,"_STopmassdn","jet_mass_pr_dn")
        self.fit_mj_single_MC(self.file_STop_mc,"_STop","ErfExpGaus_sp");
        self.fit_mj_single_MC(self.file_STop_mc,"_STopmassup","ErfExpGaus_sp");
        self.fit_mj_single_MC(self.file_STop_mc,"_STopmassdn","ErfExpGaus_sp");
        #self.fit_mlvj_model_single_MC(self.file_STop_mc,"_STop","_sb_lo","ErfPowExp_v1");
        #self.fit_mlvj_model_single_MC(self.file_STop_mc,"_STop","_signal_region","ErfPowExp_v1");

        if self.MODEL_4_mlvj=="ErfPowExp_v1":
            self.fit_mlvj_model_single_MC(self.file_STop_mc,"_STop","_sb_lo","ErfExp_v1");
            self.fit_mlvj_model_single_MC(self.file_STop_mc,"_STop","_signal_region","ErfExp_v1");
        else:
            self.fit_mlvj_model_single_MC(self.file_STop_mc,"_STop","_sb_lo",self.MODEL_4_mlvj);
            self.fit_mlvj_model_single_MC(self.file_STop_mc,"_STop","_signal_region",self.MODEL_4_mlvj);
        print "________________________________________________________________________"  

    ######## ++++++++++++++
    def fit_AllSamples_Mj_and_Mlvj(self):
        print "fit_AllSamples_Mj_and_Mlvj"
        self.fit_Signal()
        self.fit_TTbar()
        self.fit_WJets()
        self.fit_VV()
        self.fit_STop()
        print "________________________________________________________________________" 

    ####### +++++++++++++++
    def get_TTbar_controlsample(self):
        print "get_TTbar_controlsample"
        #self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_data,"_data"); #self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_data,"_data","ErfExpGaus");
        #self.saveHist("_data");

        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_STop_mc,"_STop");  
        self.fit_mj_single_MC(self.file_STop_mc,"_STop","ErfExpGaus_sp","_TTbar_controlsample");
        self.fit_mj_single_MC(self.file_STop_mc,"_STop_failtau2tau1cut","Exp","_TTbar_controlsample");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_WJets0_mc,"_WJets0");
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0","ErfExp","_TTbar_controlsample");
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0_failtau2tau1cut","Exp","_TTbar_controlsample");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_VV_mc,"_VV");     
        self.fit_mj_single_MC(self.file_VV_mc,"_VV","ErfExpGaus_sp","_TTbar_controlsample");
        self.fit_mj_single_MC(self.file_VV_mc,"_VV_failtau2tau1cut","Exp","_TTbar_controlsample");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_TTbar_mc,"_TTbar"); #self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_TTbar_mc,"_TTbar","ErfExpGaus");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_pseudodata,"_TotalMC");#self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_pseudodata,"_pseudodata","ErfExpGaus");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_data,"_data"); #self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_data,"_data","ErfExpGaus");


    ####### +++++++++++++++
    def fit_TTbar_controlsample(self):
        print "fit_TTbar_controlsample"
        #self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_data,"_data"); #self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_data,"_data","ErfExpGaus");
        #self.saveHist("_data");

        rrv_mass_j = self.workspace4fit_.var("rrv_mass_j");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_STop_mc,"_STop");  
        self.fit_mj_single_MC(self.file_STop_mc,"_STop","ErfExpGaus_sp","_TTbar_controlsample");
        self.fit_mj_single_MC(self.file_STop_mc,"_STop_failtau2tau1cut","Exp","_TTbar_controlsample");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_WJets0_mc,"_WJets0");
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0","ErfExp","_TTbar_controlsample");
        self.fit_mj_single_MC(self.file_WJets0_mc,"_WJets0_failtau2tau1cut","Exp","_TTbar_controlsample");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_VV_mc,"_VV");     
        self.fit_mj_single_MC(self.file_VV_mc,"_VV","ErfExpGaus_sp","_TTbar_controlsample");
        self.fit_mj_single_MC(self.file_VV_mc,"_VV_failtau2tau1cut","Exp","_TTbar_controlsample");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_TTbar_mc,"_TTbar"); #self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_TTbar_mc,"_TTbar","ErfExpGaus");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_pseudodata,"_TotalMC");#self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_pseudodata,"_pseudodata","ErfExpGaus");
        self.get_mj_and_mlvj_dataset_TTbar_controlsample(self.file_data,"_data"); #self.fit_mj_singlebackground_MC_TTbar_controlsample(self.file_data,"_data","ErfExpGaus");


        #self.fit_mj_TTbar_controlsample(self.file_data);
        #self.fit_mj_forPureWJet_TTbar_controlsample(self.file_data,"");
        #self.fit_mj_forPureWJet_TTbar_controlsample(self.file_data,"beforetau2tau1cut_");
        self.ScaleFactor_forPureWJet_TTbar_controlsample(self.file_data);

    ####### +++++++++++++++
    def analysis_sideband_correction_method1(self):
        self.fit_AllSamples_Mj_and_Mlvj()
        self.get_data()
        self.fit_WJetsNorm();
        self.fit_mlvj_in_Mj_sideband("_WJets1","_sb_lo", self.MODEL_4_mlvj)
        self.fit_mlvj_in_Mj_sideband("_WJets01","_sb_lo", self.MODEL_4_mlvj_alter)
        self.fit_mlvj_in_Mj_sideband("_WJets0","_sb_lo", self.MODEL_4_mlvj)
        self.prepare_limit("sideband_correction_method1")
        self.read_workspace()

    ####### +++++++++++++++
    def analysis_sideband_correction_method1_without_shape_and_psmodel_systermatic(self):
        self.fit_AllSamples_Mj_and_Mlvj()
        self.get_data()
        self.fit_WJetsNormalization_in_Mj_signal_region("_WJets0");
        self.fit_mlvj_in_Mj_sideband("_WJets0","_sb_lo", self.MODEL_4_mlvj)
        self.prepare_limit("sideband_correction_method1")
        self.read_workspace()

class doFit_wj_and_wlvj_simultaneous:
    def __init__(self):
        self.workspace4fit_ = RooWorkspace("workspace4fit_","workspace4fit_");

        self.boostedW_fitter_el=doFit_wj_and_wlvj("el","ggH600",500,700,40,130, 400., 1400., "ErfExp_v1", "ErfPow_v1", self.workspace4fit_)
        self.boostedW_fitter_mu=doFit_wj_and_wlvj("mu","ggH600",500,700,40,130, 400., 1400., "ErfExp_v1", "ErfPow_v1", self.workspace4fit_)
        self.boostedW_fitter_el.fit_TTbar_controlsample();
        self.boostedW_fitter_mu.fit_TTbar_controlsample();
        self.workspace4fit_.data("rdataset_data_mu_mj").Print(); self.workspace4fit_.data("rdataset_data_el_mj").Print();

        sample_type=RooCategory("sample_type","sample_type");
        sample_type.defineType("mu_pass");
        sample_type.defineType("mu_fail");
        sample_type.defineType("el_pass");
        sample_type.defineType("el_fail");
        rrv_weight = RooRealVar("rrv_weight","rrv_weight",0. ,10000000.) 

        rdataset_data_mu_mj=self.workspace4fit_.data("rdataset_data_mu_mj");
        rdataset_data_el_mj=self.workspace4fit_.data("rdataset_data_el_mj");
        rdataset_data_mu_mj_fail = self.workspace4fit_.data("rdataset_data_failtau2tau1cut_mu_mj"); 
        rdataset_data_el_mj_fail = self.workspace4fit_.data("rdataset_data_failtau2tau1cut_el_mj"); 

        rrv_mass_j=self.workspace4fit_.var("rrv_mass_j");
        combData_data=RooDataSet("combData_data","combData_data",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight),RooFit.Index(sample_type),RooFit.Import("mu_pass",rdataset_data_mu_mj),RooFit.Import("el_pass",rdataset_data_el_mj),RooFit.Import("mu_fail",rdataset_data_mu_mj_fail),RooFit.Import("el_fail",rdataset_data_el_mj_fail) );
        combData_data.Print();

        rdataset_TotalMC_mu_mj=self.workspace4fit_.data("rdataset_TotalMC_mu_mj");
        rdataset_TotalMC_el_mj=self.workspace4fit_.data("rdataset_TotalMC_el_mj");
        rdataset_TotalMC_mu_mj_fail = self.workspace4fit_.data("rdataset_TotalMC_failtau2tau1cut_mu_mj"); 
        rdataset_TotalMC_el_mj_fail = self.workspace4fit_.data("rdataset_TotalMC_failtau2tau1cut_el_mj"); 

        combData_TotalMC=RooDataSet("combData_TotalMC","combData_TotalMC",RooArgSet(rrv_mass_j,rrv_weight),RooFit.WeightVar(rrv_weight),RooFit.Index(sample_type),RooFit.Import("mu_pass",rdataset_TotalMC_mu_mj),RooFit.Import("el_pass",rdataset_TotalMC_el_mj),RooFit.Import("mu_fail",rdataset_TotalMC_mu_mj_fail),RooFit.Import("el_fail",rdataset_TotalMC_el_mj_fail) );
        combData_TotalMC.Print();

        # fit data
        model_data_mu=self.workspace4fit_.pdf("model_data_mu");
        model_data_fail_mu=self.workspace4fit_.pdf("model_data_failtau2tau1cut_mu");
        model_data_el=self.workspace4fit_.pdf("model_data_el");
        model_data_fail_el=self.workspace4fit_.pdf("model_data_failtau2tau1cut_el");
        simPdf_data=RooSimultaneous("simPdf_data_em","simPdf_data_em",sample_type);
        simPdf_data.addPdf(model_data_mu,"mu_pass");
        simPdf_data.addPdf(model_data_el,"el_pass");
        simPdf_data.addPdf(model_data_fail_mu,"mu_fail");
        simPdf_data.addPdf(model_data_fail_el,"el_fail");
        constrainslist_data_em=self.boostedW_fitter_el.constrainslist_data +self.boostedW_fitter_mu.constrainslist_data
        pdfconstrainslist_data_em=RooArgSet("pdfconstrainslist_data_em");
        for i in range(len(constrainslist_data_em)):
            self.workspace4fit_.pdf(constrainslist_data_em[i]).Print();
            pdfconstrainslist_data_em.add(self.workspace4fit_.pdf(constrainslist_data_em[i]) );
        pdfconstrainslist_data_em.Print();

        rfresult_data=simPdf_data.fitTo(combData_data,RooFit.Save(kTRUE),RooFit.ExternalConstraints(pdfconstrainslist_data_em) )
        rfresult_data=simPdf_data.fitTo(combData_data,RooFit.Save(kTRUE),RooFit.ExternalConstraints(pdfconstrainslist_data_em) )
        # fit TotalMC
        model_TotalMC_mu=self.workspace4fit_.pdf("model_TotalMC_mu");
        model_TotalMC_fail_mu=self.workspace4fit_.pdf("model_TotalMC_failtau2tau1cut_mu");
        model_TotalMC_el=self.workspace4fit_.pdf("model_TotalMC_el");
        model_TotalMC_fail_el=self.workspace4fit_.pdf("model_TotalMC_failtau2tau1cut_el");
        simPdf_TotalMC=RooSimultaneous("simPdf_TotalMC_em","simPdf_TotalMC_em",sample_type);
        simPdf_TotalMC.addPdf(model_TotalMC_mu,"mu_pass");
        simPdf_TotalMC.addPdf(model_TotalMC_el,"el_pass");
        simPdf_TotalMC.addPdf(model_TotalMC_fail_mu,"mu_fail");
        simPdf_TotalMC.addPdf(model_TotalMC_fail_el,"el_fail");
        constrainslist_TotalMC_em=self.boostedW_fitter_el.constrainslist_TotalMC +self.boostedW_fitter_mu.constrainslist_TotalMC
        pdfconstrainslist_TotalMC_em=RooArgSet("pdfconstrainslist_TotalMC_em");
        for i in range(len(constrainslist_TotalMC_em)):
            self.workspace4fit_.pdf(constrainslist_TotalMC_em[i]).Print();
            pdfconstrainslist_TotalMC_em.add(self.workspace4fit_.pdf(constrainslist_TotalMC_em[i]) );
        pdfconstrainslist_TotalMC_em.Print();

        rfresult_TotalMC=simPdf_TotalMC.fitTo(combData_TotalMC,RooFit.Save(kTRUE),RooFit.ExternalConstraints(pdfconstrainslist_TotalMC_em) )
        rfresult_TotalMC=simPdf_TotalMC.fitTo(combData_TotalMC,RooFit.Save(kTRUE),RooFit.ExternalConstraints(pdfconstrainslist_TotalMC_em) )

        self.boostedW_fitter_el.draw_ScaleFactor_forPureWJet_TTbar_controlsample(self.boostedW_fitter_el.file_data ,0);
        self.boostedW_fitter_mu.draw_ScaleFactor_forPureWJet_TTbar_controlsample(self.boostedW_fitter_mu.file_data, 0);


        rfresult_TotalMC.Print();
        rfresult_data.Print();

def control_sample(channel="mu"):
    print "control sample "+channel;
    #boostedW_fitter=doFit_wj_and_wlvj(channel,"ggH600",500,700,0,220) #(channel,"ggH600",500,700,40,140)
    boostedW_fitter=doFit_wj_and_wlvj(channel,"ggH600",500,700,40,130) #(channel,"ggH600",500,700,40,140)
    boostedW_fitter.fit_TTbar_controlsample();

def control_sample_simultaneous():
    print "control_sample_simultaneous";
    boostedW_fitter_sim=doFit_wj_and_wlvj_simultaneous()


def pre_limit_fitting_method(channel, higgs_sample="ggH600", in_mlvj_signal_region_min=500, in_mlvj_signal_region_max=700, in_mj_min=30, in_mj_max=140, in_mlvj_min=400, in_mlvj_max=1400): 
    print "pre_limit_fitting_method for %s sample"%(channel)
    boostedW_fitter=doFit_wj_and_wlvj(channel, higgs_sample, in_mlvj_signal_region_min, in_mlvj_signal_region_max, in_mj_min, in_mj_max, in_mlvj_min, in_mlvj_max)
    boostedW_fitter.analysis_fitting_method()

def fit_signal(method, channel, higgs_sample="ggH600", in_mlvj_signal_region_min=500, in_mlvj_signal_region_max=700, in_mj_min=30, in_mj_max=140, in_mlvj_min=400, in_mlvj_max=1400, fit_model="ErfExp_v1", fit_model_alter="ErfPow_v1"): # the WJets M_lvj shape and normalization are from sb_correction
    boostedW_fitter=doFit_wj_and_wlvj(channel, higgs_sample, in_mlvj_signal_region_min, in_mlvj_signal_region_max, in_mj_min, in_mj_max, in_mlvj_min, in_mlvj_max,fit_model, fit_model_alter);
    boostedW_fitter.fit_Signal_new()

def pre_limit_sb_correction_without_systermatic( channel, higgs_sample="ggH600", in_mlvj_signal_region_min=500, in_mlvj_signal_region_max=700, in_mj_min=30, in_mj_max=140, in_mlvj_min=400, in_mlvj_max=1400, fit_model="ErfExp_v1", fit_model_alter="ErfPow_v1"): # the WJets M_lvj shape and normalization are from sb_correction
    boostedW_fitter=doFit_wj_and_wlvj(channel, higgs_sample, in_mlvj_signal_region_min, in_mlvj_signal_region_max, in_mj_min, in_mj_max, in_mlvj_min, in_mlvj_max,fit_model, fit_model_alter);
    boostedW_fitter.analysis_sideband_correction_method1_without_shape_and_psmodel_systermatic();


def pre_limit_sb_correction(method, channel, higgs_sample="ggH600", in_mlvj_signal_region_min=500, in_mlvj_signal_region_max=700, in_mj_min=30, in_mj_max=140, in_mlvj_min=400, in_mlvj_max=1400, fit_model="ErfExp_v1", fit_model_alter="ErfPow_v1"): # the WJets M_lvj shape and normalization are from sb_correction
    print "pre_limit_sb_correction with %s for %s sample"%(method, channel)
    boostedW_fitter=doFit_wj_and_wlvj(channel, higgs_sample, in_mlvj_signal_region_min, in_mlvj_signal_region_max, in_mj_min, in_mj_max, in_mlvj_min, in_mlvj_max,fit_model, fit_model_alter);
    #boostedW_fitter.ControlPlots();
    getattr(boostedW_fitter,"analysis_sideband_correction_%s"%(method) )();
    #getattr(boostedW_fitter,"analysis_sideband_correction_method1_without_shape_and_psmodel_systermatic")();

def control_single_sb_correction(method, channel, higgs_sample="ggH600", in_mlvj_signal_region_min=500, in_mlvj_signal_region_max=700, in_mj_min=30, in_mj_max=140, in_mlvj_min=400, in_mlvj_max=1400, fit_model="ErfExp_v1", fit_model_alter="ErfPow_v1"): # the WJets M_lvj shape and normalization are from sb_correction
    print "pre_limit_sb_correction with %s for %s sample"%(method, channel)
    boostedW_fitter=doFit_wj_and_wlvj(channel, higgs_sample, in_mlvj_signal_region_min, in_mlvj_signal_region_max, in_mj_min, in_mj_max, in_mlvj_min, in_mlvj_max,fit_model, fit_model_alter);
    boostedW_fitter.ControlPlots();

def pre_limit_simple(channel):
    print "pre_limit_simple for %s sampel"%(channel)
    pre_limit_sb_correction_without_systermatic(channel, "ggH600",550,700,40,130,400,1000,"ErfPowExp_v1","ErfPow2_v1");
    #pre_limit_sb_correction_without_systermatic(channel, "ggH700",550,700,40,130,400,1000,"ErfPowExp_v1","ErfPow2_v1");
    #pre_limit_sb_correction_without_systermatic(channel,"ggH800",550,1000,40,130,600,1400,"Exp","Pow")
    #pre_limit_sb_correction_without_systermatic(channel,"ggH900",800,1150,40,130,600,1400,"Exp","Pow")
    #pre_limit_sb_correction_without_systermatic(channel,"ggH1000",800,1150,40,130,600,1400,"Exp","Pow")
    #pre_limit_sb_correction_without_systermatic(channel,"ggH1500",1200,1800,40,130,1000,2000,"Exp","Pow")
    #pre_limit_sb_correction_without_systermatic(channel,"ggH2000",1500,2500,40,130,1200,2800,"Exp","Pow")
  
def Fit_Signal(channel):
    fit_signal("method1",channel, "ggH600",500,700,30,140,200,1400,"ErfExp_v1")
    fit_signal("method1",channel, "ggH700",500,700,30,140,200,1400,"ErfExp_v1")
    fit_signal("method1",channel, "ggH800",500,700,30,140,200,2000,"ErfExp_v1")
    fit_signal("method1",channel, "ggH900",500,700,30,140,200,2000,"ErfExp_v1")
    fit_signal("method1",channel,"ggH1000",500,700,30,140,200,2800,"Exp")
  
def control_single(channel):
    print "control_single for %s sampel"%(channel)
    #control_single_sb_correction("method1",channel, "ggH600",500,700,30,140,400,1000,"ErfExp_v1")
    control_single_sb_correction("method1",channel, "ggH600",500,1300,20,130,400,1400,"ErfExp_v1")

def check_workspace(channel, higgs):
    boostedW_fitter=doFit_wj_and_wlvj(channel,higgs); boostedW_fitter.read_workspace()

if __name__ == '__main__':
    channel=options.channel;#mu or el; default is mu;


    if options.fitwtagger:
        print 'fitwtagger for %s sample'%(channel)
        control_sample(channel);#mu for muon sample; el for el sample
 
    if options.fitwtaggersim:
        print 'fitwtagger for el+mu sample'
        control_sample_simultaneous();#mu for muon sample; el for el sample
        
    if options.control:
        print 'control for %s sample'%(channel);
        control_single(channel);

    if options.fitsignal:
        print "fitsignal"
        Fit_Signal(channel);

    if options.check:
        print 'check workspace for %s sample'%(channel);
        check_workspace(channel,"ggH600");

    if options.simple and (not options.fitwtagger) and (not options.fitwtaggersim) and ( not options.multi) and ( not options.control) and ( not options.check) and (not options.fitsignal):
        print 'simple mode for %s sample'%(channel)
        pre_limit_simple(channel);

    if options.multi:
        print 'multi mode for %s sample'%(channel)
        pre_limit_sb_correction("method1",sys.argv[1],sys.argv[2],int(sys.argv[3]),int(sys.argv[4]),int(sys.argv[5]),int(sys.argv[6]),int(sys.argv[7]),int(sys.argv[8]), sys.argv[9], sys.argv[10] )