Merge pull request #15 from RazorCMS/jan-9-mods

Jan 9 mods

Author: jaylawhorn

config/run2_2017_01_07_Run2016G_SUSYUnblind_Sep23ReReco.config

@@ -89,7 +89,7 @@ combine_pdfs = ['RooRazor3DBinPdf::DiJet_TTj0b(th1x,MR0_TTj0b_DiJet,R0_TTj0b_DiJ
 
 #signal and plotting binning
 #signal_MR =  [500, 600, 700, 900, 1200, 1600, 2500, 4000]
-signal_MR =  [500, 575, 650, 700, 900, 1200, 1600, 2500, 4000]
+signal_MR =  [500, 575, 650, 750, 900, 1200, 1600, 2500, 4000]
 #signal_Rsq = [0.25,0.30,0.41,0.52,0.64,0.8,1.5]
 signal_Rsq = [0.25,0.30,0.41,0.52,0.64,1.5]
 signal_nBtag = [0.,1.,2.,3.]
@@ -99,8 +99,8 @@ signal_nBtag = [0.,1.,2.,3.]
 variables = ['MR[400.,400.,4000.]', 'Rsq[0.15,0.15,1.5]', 'nBtag[0.,0.,4.]']
 
 variables_range = ['MR_LowRsq[400.,4000.]', 'Rsq_LowRsq[0.15,0.2]', 'nBtag_LowRsq[0.,4.]',
-		   'MR_LowMR[400.,500.]', 'Rsq_LowMR[0.2,1.5]', 'nBtag_LowMR[0.,4.]',
-		   'MR_HighMR[500.,4000.]', 'Rsq_HighMR[0.2,1.5]', 'nBtag_HighMR[0.,4.]']
+		   'MR_LowMR[400.,550.]', 'Rsq_LowMR[0.2,1.5]', 'nBtag_LowMR[0.,4.]',
+		   'MR_HighMR[550.,4000.]', 'Rsq_HighMR[0.2,1.5]', 'nBtag_HighMR[0.,4.]']
 
 parameters = ['MR0_TTj0b[-900.05]', 'R0_TTj0b[-0.7]', 'b_TTj0b[1.4]','n_TTj0b[3.7]',
 	      'MR0_TTj1b[-900.05]', 'R0_TTj1b[-0.7]', 'b_TTj1b[1.4]','n_TTj1b[3.7]',
@@ -142,7 +142,8 @@ combine_pdfs = ['RooRazor3DBinPdf::LeptonMultiJet_TTj0b(th1x,MR0_TTj0b_LeptonMul
 		'SUM::extRazorPdf(Ntot_TTj0b_LeptonMultiJet*LeptonMultiJet_TTj0b,Ntot_TTj1b_LeptonMultiJet*LeptonMultiJet_TTj1b,Ntot_TTj2b_LeptonMultiJet*LeptonMultiJet_TTj2b,Ntot_TTj3b_LeptonMultiJet*LeptonMultiJet_TTj3b)']
 
 #signal and plotting binning
-signal_MR =  [400, 500, 600, 700, 900, 1200, 1600, 2500, 4000]
+#signal_MR =  [400, 500, 600, 700, 900, 1200, 1600, 2500, 4000]
+signal_MR =  [400, 475, 550, 700, 900, 1200, 1600, 2500, 4000]
 #signal_Rsq = [0.15,0.20,0.25,0.30,0.41,0.52,0.64,0.8,1.5]
 signal_Rsq = [0.15,0.20,0.25,0.30,0.41,0.52,0.64,1.5]
 signal_nBtag = [0.,1.,2.,3.,4.]
@@ -188,7 +189,7 @@ combine_pdfs = ['RooRazor3DBinPdf::LeptonJet_TTj0b(th1x,MR0_TTj0b_LeptonJet,R0_T
 
 #signal and plotting binning
 #signal_MR =  [400, 500, 600, 700, 900, 1200, 1600, 2500, 4000]
-signal_MR =  [400, 475, 550, 600, 700, 900, 1200, 1600, 2500, 4000]
+signal_MR =  [400, 475, 550, 700, 900, 1200, 1600, 2500, 4000]
 #signal_Rsq = [0.15,0.20,0.25,0.30,0.41,0.52,0.64,0.8,1.5]
 signal_Rsq = [0.15,0.20,0.25,0.30,0.41,0.52,0.64,1.5]
 signal_nBtag = [0.,1.,2.,3.]

python/BinnedFit.py

@@ -14,7 +14,7 @@
 
 densityCorr = False
 
-def binnedFit(pdf, data, fitRange='Full',useWeight=False, box='MultiJet'):
+def binnedFit(pdf, data, fitRange='Full',useWeight=False):
 
     if useWeight:
         fr = pdf.fitTo(data,rt.RooFit.Range(fitRange),rt.RooFit.Extended(True),rt.RooFit.SumW2Error(True),rt.RooFit.Save(),rt.RooFit.Minimizer('Minuit2','migrad'),rt.RooFit.Strategy(2))
@@ -47,8 +47,6 @@ def binnedFit(pdf, data, fitRange='Full',useWeight=False, box='MultiJet'):
         hesse_status = 3
         migrad_status = 3
 
-        print box
-
         if box=='MultiJet':
             migrad_status = m2.minimize('Minuit2','migrad')
             improve_status = m2.minimize('Minuit2','improve')
@@ -63,14 +61,16 @@ def binnedFit(pdf, data, fitRange='Full',useWeight=False, box='MultiJet'):
             simplex_status = m2.minimize('Minuit2', 'simplex')
             simplex_status = m2.minimize('Minuit2', 'simplex')
             migrad_status = m2.minimize('Minuit2','migrad')
+            improve_status = m2.minimize('Minuit2','improve')
+            migrad_status = m2.minimize('Minuit2','migrad')
+            migrad_status = m2.minimize('Minuit2','migrad')
             hesse_status = m2.minimize('Minuit2','hesse')
 
         elif box=='LeptonMultiJet':
             scan_status = m2.minimize('Minuit2', 'scan')
             scan_status = m2.minimize('Minuit2', 'scan')
-            simplex_status = m2.minimize('Minuit2', 'simplex')
-            simplex_status = m2.minimize('Minuit2', 'simplex')
-            simplex_status = m2.minimize('Minuit2', 'simplex')
+            migrad_status = m2.minimize('Minuit2','migrad')
+            improve_status = m2.minimize('Minuit2','improve')
             migrad_status = m2.minimize('Minuit2','migrad')
             migrad_status = m2.minimize('Minuit2','migrad')
             hesse_status = m2.minimize('Minuit2','hesse')

python/PlotFit.py

@@ -472,7 +472,12 @@ def getBestFitRms(myTree, sumName, nObs, d, options, plotName):
 
     if pvalue <= 0.:
         print "pvalue = 0 from histogram method: reverting to gaussian approximation"
-        nsigma = (nObs-bestFit)/rms
+        #print rms
+        if rms<=0:
+            print "rms==0, this is sad"
+            nsigma = 100
+        else:
+            nsigma = (nObs-bestFit)/rms
         pvalue = 2.*rt.Math.gaussian_cdf_c(abs(nsigma))
     print '%s, bestFit %f, mean %.1f, mode %.1f, rms %.1f, pvalue %f, nsigma %.1f'%(sumName, bestFit,mean,mode,rms,pvalue,nsigma)
 
@@ -775,7 +780,7 @@ def print1DProj(c,rootFile,h,h_data,printName,xTitle,yTitle,lumiLabel="",boxLabe
     c.Write(os.path.splitext(printName)[0].split('/')[-1])
 
 
-def print1DProjNs(c,rootFile,h,h_data,h_ns,printName,xTitle,yTitle,lumiLabel="",boxLabel="",plotLabel="",isData=False,doSignalInj=False,options=None,tLeg=None,h_components=[],h_colors=[],h_labels=[],cfg=None):
+def print1DProjNs(c,rootFile,h,h_data,h_ns,printName,xTitle,yTitle,lumiLabel="",boxLabel="",plotLabel="",isData=False,doSignalInj=False,options=None,tLeg=None,h_components=[],h_colors=[],h_labels=[]):
 
     if densityCorr:
         h_densitycorr = densityCorrect(h)