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makingSpecPlots.py
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makingSpecPlots.py
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from __future__ import absolute_import, division, print_function
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import argparse
import os
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras.models import load_model
import DSNNr_5050 as DSNNr
from collections import defaultdict
from tensorflow.keras.utils import to_categorical
from sklearn.model_selection import train_test_split
# Global plot settings
from matplotlib import rc
import matplotlib.font_manager
from calibration import HistogramCalibrator
from ROOT import TH2F, TCanvas, TH1F, gROOT, gStyle, TLegend, TLorentzVector, TPad, TLine, gPad, TGraphErrors, TLatex, TFile
import ROOT as ROOT
import root_numpy as rn
import math
from numpy import argmax
from array import array
from numpy import load
rc("font", family="serif")
rc("text", usetex=False)
rc("font", size=22)
rc("xtick", labelsize=15)
rc("ytick", labelsize=15)
rc("legend", fontsize=7.5)
ROOT.PyConfig.IgnoreCommandLineOptions = True # stop PyRoot hijacking -h WHY DOESNT THIS ALWAYS WORK
ROOT.gROOT.SetBatch(True) # Don't want to plot these to screen as we generate them
ROOT.gROOT.SetStyle('ATLAS')
# Remove stat box
gStyle.SetOptStat(0)
gStyle.SetTitleFontSize(0.08)
gStyle.SetLabelSize(0.1)
model = keras.models.load_model("/hpcgpfs01/scratch/ftsai/DSNNrBranch/ImprovingTraining/saved_models_fix3rdJet_P110105100F95_7layers/model-055.ckpt")
#MCa
#mBB,pTV,dRBB,nJ,dEtaBB,dPhiVBB,dPhiLBmin,dYWH,mTW,pTB1,pTB2,Mtop,met_met,nTags,sumPtJets,HTBoosted,HT_bdtr
obs = ["mBB","pTV","dRBB","nJ","dEtaBB"]
obs_axis = ["m(jet,jet) [GeV]","pTV [GeV]","dR(jet,jet)","nJ","dEta(jet,jet)"]
# obs_idx = 0
inputMCaFile = '/hpcgpfs01/scratch/ftsai/DSNNrBranch/ImprovingTraining/SherpaOutputs.npz'
MCa = np.load(inputMCaFile)["MCa"]
eventRunA=len(MCa)
MCa_spec = np.load(inputMCaFile)["MCa_spec"]
MCa_weights = np.load(inputMCaFile)["MCa_weights"]
#MCb
inputMCbFile = '/hpcgpfs01/scratch/ftsai/DSNNrBranch/ImprovingTraining/MGPy8Outputs.npz'
MCb = np.load(inputMCbFile)["MCb"]
eventRun = len(MCb)
MCb_spec = np.load(inputMCbFile)["MCb_spec"]
MCb_weights = np.load(inputMCbFile)["MCb_weights"]
features = ['pt','eta','phi','m']
PATHtoSplitFile = '/hpcgpfs01/scratch/ftsai/DSNNr4gpu/DSNNDemo/'
with np.load(PATHtoSplitFile+'DataMCadeSplit5050jetFlav_ID.npz', allow_pickle=True, mmap_mode='r') as data3:
spec_test = data3["S_test"]
Y_test = data3["Y_test"]
Y_train = data3["Y_train"]
W_test = data3["W_test"]
W_train = data3["W_train"]
X_test = data3["X_test"]
X_train = data3["X_train"]
Y_train = argmax(Y_train, axis=1)
Y_test = argmax(Y_test,axis=1)
Y_test = argmax(Y_test,axis=1)
Y_train = argmax(Y_train, axis=1)
for obs_idx in range(0, 2):
MCa_spec_mBB = MCa_spec[:,obs_idx][:eventRunA] #mBB,pTV,dRBB,nJ,dEtaBB
MCa_weights = MCa_weights[:eventRunA]
MCa_spec_nJ = MCa_spec[:,3][:eventRunA]
MCa_spec = MCa_spec[:eventRunA]
MCa_ntags = MCa_spec[:,13][:eventRunA]
filter_2J_MCa = np.logical_and(MCa_spec_nJ==2, MCa_ntags==2)
filter_3J_MCa = np.logical_and(MCa_spec_nJ==3, MCa_ntags==2)
MCb_spec_mBB = MCb_spec[:,obs_idx][:eventRun]
MCb_weights = MCb_weights[:eventRun]
MCb_spec_nJ = MCb_spec[:,3][:eventRun]
MCb_spec = MCb_spec[:eventRun]
MCb_ntags = MCb_spec[:,13][:eventRun]
filter_MCb = MCb_spec_mBB[MCb_ntags==2]
filter_2J_MCb = np.logical_and(MCb_spec_nJ==2, MCb_ntags==2)
filter_3J_MCb = np.logical_and(MCb_spec_nJ==3, MCb_ntags==2)
#spec_train_MCa_mBB = spec_train[:,0][Y_train == 0]
#print("spec_train_MCa_mBB:{}".format(spec_train_MCa_mBB))
spec_test_MCa_mBB_all = spec_test[:,obs_idx][Y_test==0]
filter_test_mBB = spec_test[:,obs_idx][Y_test==0]
#filter_test_2jets_mBB = np.logical_and(np.logical_and(spec_test[:,obs_idx][Y_test==0], spec_test[:,3][Y_test==0]==2), spec_test[:,13][Y_test==0]==2)
#filter_test_3jets_mBB = np.logical_and(np.logical_and(spec_test[:,obs_idx][Y_test==0], spec_test[:,3][Y_test==0]==3), spec_test[:,13][Y_test==0]==2)
filter_test_2jets_mBB = np.logical_and(spec_test[:,obs_idx][Y_test==0], spec_test[:,3][Y_test==0]==2)
filter_test_3jets_mBB = np.logical_and(spec_test[:,obs_idx][Y_test==0], spec_test[:,3][Y_test==0]==3)
spec_test_MCa_mBB = spec_test[:,obs_idx][Y_test==0]
spec_test_2jets_mBB = spec_test_MCa_mBB_all[filter_test_2jets_mBB]
spec_test_3jets_mBB = spec_test_MCa_mBB_all[filter_test_3jets_mBB]
X_train_MCa = X_train[Y_train == 0]
X_train_MCb = X_train[Y_train == 1]
X_test_MCa = X_test[Y_test == 0]
X_test_MCb = X_test[Y_test == 1]
train_weights_MCa = W_train[Y_train == 0]
test_weights_MCa = W_test[Y_test == 0]
preds_train = model.predict(X_train_MCa)
preds_train_b = model.predict(X_train_MCb)
preds_test_b = model.predict(X_test_MCb)
NNweights_train = preds_train[:, 1] / preds_train[:, 0]
preds_test = model.predict(X_test_MCa)
#preds_test_b = model.predict(X_test_MCb)
calibrator = HistogramCalibrator(preds_train[:, 0], preds_train_b[:, 0])
#calibrator = HistogramCalibrator(preds_train[:, 0], preds_train_b[:, 0], histrange=[0,1])
Prob_MCa_test = preds_test[:, 0].flatten()
#Prob_MCa_test = Prob_MCa_test.tolist()
Cali_PA, Cali_a = calibrator.cali_pred(preds_test[:, 0])
Cali_PA = np.ma.masked_invalid(Cali_PA)
Cali_a = np.ma.masked_invalid(Cali_a)
#NNweights_test = preds_test[:, 1] / preds_test[:, 0]
NNweights_test = Cali_a/Cali_PA
#weightTrainR_expand = NNweights_train * train_weights_MCa
weightTestR_expand = NNweights_test * test_weights_MCa
weightTestR_expand_2jets = NNweights_test[filter_test_2jets_mBB] * test_weights_MCa[filter_test_2jets_mBB]
weightTestR_expand_3jets = NNweights_test[filter_test_3jets_mBB] * test_weights_MCa[filter_test_3jets_mBB]
nBins = 20
if obs_idx == 0:
minElem = 25
maxElem = 500
if obs_idx == 1:
minElem = 0
maxElem = 2000
if obs_idx == 2:
minElem = 0.5
maxElem = 6
#maxElem = np.amax(spec_train_MCa_mBB)
histMbb_MCa = TH1F("mBB_MCa", "mBB_MCa", nBins, minElem, maxElem)
histMbb_MCb = TH1F("mBB_MCb", "mBB_MCb", nBins, minElem, maxElem)
trainMbb_rMCa = TH1F("mBB_train", "mBB_train", nBins, minElem, maxElem)
testMbb_rMCa = TH1F("mBB_test", "mBB_test", nBins, minElem, maxElem)
allJet2D = TH2F("allJet2D", "observable", 100, 0.32, 0.85, 100, 0.32, 0.85)
#maxElem_2 = np.amax(MCb_spec_mBB[MCb_spec_nJ==2])
histMbb_MCa_2jets = TH1F("mBB_MCa_2jets", "mBB_MCa_2jets", nBins, minElem, maxElem)
histMbb_MCb_2jets = TH1F("mBB_MCb_2jets", "mBB_MCb_2jets", nBins, minElem, maxElem)
testMbb_rMCa_2jets = TH1F("mBB_test_2jets", "mBB_test_2jets", nBins, minElem, maxElem)
#maxElem_3 = np.amax(MCb_spec_mBB[MCb_spec_nJ==3])
histMbb_MCa_3jets = TH1F("mBB_MCa_3jets", "mBB_MCa_3jets", nBins, minElem, maxElem)
histMbb_MCb_3jets = TH1F("mBB_MCb_3jets", "mBB_MCb_3jets", nBins, minElem, maxElem)
testMbb_rMCa_3jets = TH1F("mBB_test_3jets", "mBB_test_3jets", nBins, minElem, maxElem)
if obs_idx == 0:
binNum = 17
#newbins_1 = [25,35,45,55,75,125,200,300,400,500]
newbins_1 = [25,50,75,100,125,150,175,200,225,250,275,300,325,350,375,400,450,500]
if obs_idx == 1:
binNum = 7
newbins_1 = [0,100,125,150,200,300,400,2000]
if obs_idx == 2:
binNum = 16
newbins_1 = [0.5,0.75,1.0,1.25,1.5,1.75,2.0,2.25,2.5,2.75,3.0,3.25,3.5,3.75,4.0,5.0,6.0]
newbins_array_1 = array('d', newbins_1)
histMbb_MCa = histMbb_MCa.Rebin(binNum, "rebinned_mBB_MCa", newbins_array_1)
histMbb_MCb = histMbb_MCb.Rebin(binNum, "rebinned_mBB_MCb", newbins_array_1)
testMbb_rMCa = testMbb_rMCa.Rebin(binNum, "rebinned_mBB_test", newbins_array_1)
histMbb_MCa_2jets = histMbb_MCa_2jets.Rebin(binNum, "rebinned_MCa_2jets", newbins_array_1)
histMbb_MCb_2jets = histMbb_MCb_2jets.Rebin(binNum, "rebinned_MCb_2jets", newbins_array_1)
testMbb_rMCa_2jets = testMbb_rMCa_2jets.Rebin(binNum, "rebinned_test_2jets", newbins_array_1)
histMbb_MCa_3jets = histMbb_MCa_3jets.Rebin(binNum, "rebinned_MCa_3jets", newbins_array_1)
histMbb_MCb_3jets = histMbb_MCb_3jets.Rebin(binNum, "rebinned_MCb_3jets", newbins_array_1)
testMbb_rMCa_3jets = testMbb_rMCa_3jets.Rebin(binNum, "rebinned_test_3jets", newbins_array_1)
##all jets
rn.fill_hist(histMbb_MCa, MCa_spec_mBB, MCa_weights)
rn.fill_hist(histMbb_MCb, MCb_spec_mBB, MCb_weights)
#rn.fill_hist(trainMbb_rMCa, spec_train_MCa_mBB, weightTrainR_expand)
rn.fill_hist(testMbb_rMCa, spec_test_MCa_mBB, weightTestR_expand)
### Fill a 2D plot
#data = np.column_stack((Cali_PA, Prob_MCa_test))
#data = np.column_stack((Cali_PA, spec_test_MCa_mBB * weightTestR_expand))
#rn.fill_hist(allJet2D, data)
#canvas = TCanvas("canvas", "2D Histogram", 800, 600)
#canvas.SetLogx()
#allJet2D.Draw("colz")
#canvas.SaveAs("2Dplot.pdf")
##2 jets
rn.fill_hist(histMbb_MCa_2jets, MCa_spec_mBB[MCa_spec_nJ==2], MCa_weights[MCa_spec_nJ==2])
rn.fill_hist(histMbb_MCb_2jets, MCb_spec_mBB[MCb_spec_nJ==2], MCb_weights[MCb_spec_nJ==2])
rn.fill_hist(testMbb_rMCa_2jets, spec_test_2jets_mBB, weightTestR_expand_2jets)
## 3 jets
rn.fill_hist(histMbb_MCa_3jets, MCa_spec_mBB[MCa_spec_nJ==3], MCa_weights[MCa_spec_nJ==3])
rn.fill_hist(histMbb_MCb_3jets, MCb_spec_mBB[MCb_spec_nJ==3], MCb_weights[MCb_spec_nJ==3])
rn.fill_hist(testMbb_rMCa_3jets, spec_test_3jets_mBB, weightTestR_expand_3jets)
histMbb_MCa.Scale(1/histMbb_MCa.Integral())
histMbb_MCb.Scale(1/histMbb_MCb.Integral())
#trainMbb_rMCa.Scale(1/trainMbb_rMCa.Integral())
testMbb_rMCa.Scale(1/testMbb_rMCa.Integral())
histMbb_MCa_2jets.Scale(1/histMbb_MCa_2jets.Integral())
histMbb_MCb_2jets.Scale(1/histMbb_MCb_2jets.Integral())
testMbb_rMCa_2jets.Scale(1/testMbb_rMCa_2jets.Integral())
histMbb_MCa_3jets.Scale(1/histMbb_MCa_3jets.Integral())
histMbb_MCb_3jets.Scale(1/histMbb_MCb_3jets.Integral())
testMbb_rMCa_3jets.Scale(1/testMbb_rMCa_3jets.Integral())
can1 = TCanvas("mBB","mBB")
mainPad = TPad("mainPad", "top", 0.02, 0.45, 0.98, 0.98)
ratioPad = TPad("ratioPad","bottom", 0.02, 0.08, 0.98, 0.45) #(,0.02,,)
mainPad.SetBottomMargin(0.01)
ratioPad.SetTopMargin(0.04)
ratioPad.SetBottomMargin(0.15)
#mainPad.SetLogy()
mainPad.Draw()
mainPad.cd()
histMbb_MCa.GetYaxis().SetTitle("#frac{d#sigma}{d"+obs[obs_idx]+"}")
histMbb_MCa.SetFillColorAlpha(ROOT.kAzure+7, 0.25)
histMbb_MCa.SetLineColor(ROOT.kAzure+7)
histMbb_MCa.GetYaxis().SetTitleSize(0.04)
histMbb_MCa.GetYaxis().SetLabelSize(0.02)
histMbb_MCa.GetXaxis().SetLabelSize(0.02)
histMbb_MCa.GetYaxis().SetTitleOffset(0.7)
histMbb_MCa.DrawCopy("hist")
histMbb_MCb.GetYaxis().SetTitle("#frac{d#sigma}{d"+obs[obs_idx]+"}")
histMbb_MCb.SetFillColorAlpha(ROOT.kOrange-3, 0.25)
histMbb_MCb.SetLineColor(ROOT.kOrange-3)
histMbb_MCb.GetYaxis().SetTitleSize(0.04)
histMbb_MCb.GetYaxis().SetLabelSize(0.02)
histMbb_MCb.GetXaxis().SetLabelSize(0.02)
histMbb_MCb.GetYaxis().SetTitleOffset(0.7)
histMbb_MCb.DrawCopy("hist SAME")
testMbb_rMCa.SetFillColorAlpha(ROOT.kBlue, 0.25)
testMbb_rMCa.SetLineColor(ROOT.kBlue)
testMbb_rMCa.GetYaxis().SetTitleSize(0.04)
testMbb_rMCa.GetYaxis().SetLabelSize(0.02)
testMbb_rMCa.GetXaxis().SetLabelSize(0.02)
testMbb_rMCa.DrawCopy("hist SAME")
tt1 = ROOT.TLatex()
tt1.SetNDC()
tt1.SetTextSize(0.07)
tt1.DrawLatex(0.35 ,0.75 ,"p-value(test, MCb):"+str(format(testMbb_rMCa.Chi2Test(histMbb_MCb,"WW P"),'.1E')))
tt2 = ROOT.TLatex()
tt2.SetNDC()
tt2.SetTextSize(0.055)
#tt2.DrawLatex(0.45 ,0.70 ,"p-value(train, MCb):"+str(format(trainMbb_rMCa.Chi2Test(histMbb_MCb,"WW P"),'.1E')))
tt3 = ROOT.TLatex()
tt3.SetNDC()
tt3.SetTextSize(0.07)
tt3.DrawLatex(0.35 ,0.60 ,"p-value(MCa, MCb):"+str(format(histMbb_MCa.Chi2Test(histMbb_MCb,"WW P"),'.1E')))
legend = TLegend(0.64,0.65,0.95,0.85)
legend.SetBorderSize(0)
legend.AddEntry(histMbb_MCb, "MGPy8", "l")
legend.AddEntry(histMbb_MCa, "Sherpa", "l")
legend.AddEntry(testMbb_rMCa, "Sherpa(testing) * NN", "l")
#legend.AddEntry(trainMbb_rMCa, "MCa(training) * NN", "l")
n_ex=[]
n_ey=[]
n_x=[]
n_y=[]
for hisBin in range(histMbb_MCa.GetNbinsX()+1):
if hisBin==0: continue
n_x.append(histMbb_MCa.GetBinLowEdge(hisBin)+ 0.5*(histMbb_MCa.GetBinLowEdge(hisBin+1)-(histMbb_MCa.GetBinLowEdge(hisBin))))
n_y.append(1) #center at 1 in the y-axis
n_ex.append((histMbb_MCa.GetBinLowEdge(hisBin+1)-histMbb_MCa.GetBinLowEdge(hisBin))*0.5)
if testMbb_rMCa.GetBinContent(hisBin)+histMbb_MCb.GetBinError(hisBin)!=0:
n_ey.append(math.sqrt(pow(histMbb_MCb.GetBinError(hisBin),2)+pow(testMbb_rMCa.GetBinError(hisBin),2))/(histMbb_MCb.GetBinContent(hisBin)+testMbb_rMCa.GetBinContent(hisBin)))
else:
n_ey.append(2)
gr = TGraphErrors(binNum,np.array(n_x, dtype=float),np.array(n_y, dtype=float),np.array(n_ex, dtype=float),np.array(n_ey, dtype=float))
gr.GetXaxis().SetLimits(minElem,maxElem)
gr.GetYaxis().CenterTitle(1)
gr.GetYaxis().SetTitleOffset(0.25)
gr.GetYaxis().SetTitleSize(0.1)
gr.GetXaxis().SetTitle(obs_axis[obs_idx])
gr.GetXaxis().SetTitleOffset(0.55)#0.25
gr.GetXaxis().SetTitleSize(0.10)
gr.GetYaxis().SetLabelSize(0.02)
gr.GetXaxis().SetLabelSize(0.04)
gr.SetMarkerStyle(1)
gr.SetFillColorAlpha(ROOT.kPink+6, 0.25)
gr.SetLineColor(ROOT.kPink+6)
gr.GetYaxis().SetTitle("w.r.t MGPy8")
gr.GetYaxis().SetRangeUser(0.5,1.5)
legend.AddEntry(gr, "(Test+MCb)Stat Unc.")
legend.SetTextSize(0.045)
legend.Draw()
can1.cd()
ratioPad.Draw()
ratioPad.cd()
gr.Draw("a2")
line = TLine(0,1,maxElem,1)
line.SetLineWidth(2)
line.SetLineStyle(2)
line.Draw("SAME")
ratio_baseline = histMbb_MCa.Clone("ratio_hista")
ratio_baseline.Divide(histMbb_MCb)
ratio_baseline.SetFillColorAlpha(0, 0.25)
ratio_baseline.SetMarkerStyle(86)
ratio_baseline.SetMarkerColor(ROOT.kAzure+7)
ratio_baseline.SetMarkerSize(0.7)
ratio_baseline2 = testMbb_rMCa.Clone("ratio_histr_test")
ratio_baseline2.Divide(histMbb_MCb)
ratio_baseline2.SetMarkerColor(ROOT.kBlue)
ratio_baseline2.SetMarkerSize(0.7)
ratio_baseline2.GetYaxis().SetRangeUser(0.5,1.5)
ratio_baseline2.GetYaxis().CenterTitle(1)
ratio_baseline2.GetYaxis().SetTitleOffset(0.5)
ratio_baseline2.GetYaxis().SetTitle("w.r.t MGPy8")
ratio_baseline2.GetYaxis().SetTitleSize(0.1)
ratio_baseline2.GetXaxis().SetTitle(obs_axis[obs_idx])
ratio_baseline2.GetXaxis().SetTitleOffset(0.55) #0.25
ratio_baseline2.GetXaxis().SetTitleSize(0.15) #0.1
ratio_baseline2.GetYaxis().SetLabelSize(0.04)
ratio_baseline2.Draw("hist p SAME")
ratio_baseline.Draw("hist p SAME")
myfile = TFile('h_'+obs[obs_idx]+'_jflav_test7.root', 'RECREATE')
ratio_baseline.Write()
ratio_baseline2.Write()
myfile.Close()
can1.cd()
can1.Draw()
can1.Update()
can1.SaveAs("Spec/Obs_"+obs[obs_idx]+"_Demo.png")
can1.Close()
can2 = TCanvas("mBB_2jet","mBB")
mainPad_2 = TPad("mainPad_2", "top_2", 0.02, 0.45, 0.98, 0.98)
ratioPad_2 = TPad("ratioPad_2","bottom_2", 0.02, 0.08, 0.98, 0.45)
mainPad_2.SetBottomMargin(0.01)
ratioPad_2.SetTopMargin(0.04)
ratioPad_2.SetBottomMargin(0.15)
#mainPad_2.SetLogy()
mainPad_2.Draw()
mainPad_2.cd()
histMbb_MCa_2jets.GetYaxis().SetTitle("#frac{d#sigma}{"+obs[obs_idx]+"}")
histMbb_MCa_2jets.SetFillColorAlpha(ROOT.kAzure+7, 0.25)
histMbb_MCa_2jets.SetLineColor(ROOT.kAzure+7)
histMbb_MCa_2jets.GetYaxis().SetTitleSize(0.04)
histMbb_MCa_2jets.GetYaxis().SetLabelSize(0.02)
histMbb_MCa_2jets.GetXaxis().SetLabelSize(0.02)
histMbb_MCa_2jets.GetYaxis().SetTitleOffset(0.7)
histMbb_MCa_2jets.DrawCopy("hist")
histMbb_MCb_2jets.GetYaxis().SetTitle("#frac{d#sigma}{d"+obs[obs_idx]+"}")
histMbb_MCb_2jets.SetFillColorAlpha(ROOT.kOrange-3, 0.25)
histMbb_MCb_2jets.SetLineColor(ROOT.kOrange-3)
histMbb_MCb_2jets.GetYaxis().SetTitleSize(0.04)
histMbb_MCb_2jets.GetYaxis().SetLabelSize(0.02)
histMbb_MCb_2jets.GetXaxis().SetLabelSize(0.02)
histMbb_MCb_2jets.GetYaxis().SetTitleOffset(0.7)
histMbb_MCb_2jets.DrawCopy("hist SAME")
testMbb_rMCa_2jets.SetFillColorAlpha(ROOT.kBlue, 0.25)
testMbb_rMCa_2jets.SetLineColor(ROOT.kBlue)
testMbb_rMCa_2jets.GetYaxis().SetTitleSize(0.04)
testMbb_rMCa_2jets.GetYaxis().SetLabelSize(0.02)
testMbb_rMCa_2jets.GetXaxis().SetLabelSize(0.02)
testMbb_rMCa_2jets.DrawCopy("hist SAME")
tt1 = ROOT.TLatex()
tt1.SetNDC()
tt1.SetTextSize(0.055)
tt1.DrawLatex(0.35 ,0.75 ,"p-value(test, MCb):"+str(format(testMbb_rMCa_2jets.Chi2Test(histMbb_MCb_2jets,"WW P"),'.1E')))
tt2 = ROOT.TLatex()
tt2.SetNDC()
tt2.SetTextSize(0.055)
#tt2.DrawLatex(0.45 ,0.70 ,"p-value(train, MCb):"+str(format(trainMbb_rMCa.Chi2Test(histMbb_MCb,"WW P"),'.1E')))
tt3 = ROOT.TLatex()
tt3.SetNDC()
tt3.SetTextSize(0.055)
tt3.DrawLatex(0.35 ,0.65 ,"p-value(MCa, MCb):"+str(format(histMbb_MCa_2jets.Chi2Test(histMbb_MCb_2jets,"WW P"),'.1E')))
legend = TLegend(0.64,0.65,0.95,0.85)
legend.SetBorderSize(0)
legend.AddEntry(histMbb_MCb_2jets, "MGPy8 (2jets)", "l")
legend.AddEntry(histMbb_MCa_2jets, "Sherpa (2jets)", "l")
legend.AddEntry(testMbb_rMCa_2jets, "Sherpa(testing_2jets) * NN", "l")
#legend.AddEntry(trainMbb_rMCa, "MCa(training) * NN", "l")
n_ex=[]
n_ey=[]
n_x=[]
n_y=[]
for hisBin in range(histMbb_MCa_2jets.GetNbinsX()+1):
if hisBin==0: continue
n_x.append(histMbb_MCa_2jets.GetBinLowEdge(hisBin)+ 0.5*(histMbb_MCa_2jets.GetBinLowEdge(hisBin+1)-(histMbb_MCa_2jets.GetBinLowEdge(hisBin))))
n_y.append(1) #center at 1 in the y-axis
n_ex.append((histMbb_MCa_2jets.GetBinLowEdge(hisBin+1)-histMbb_MCa_2jets.GetBinLowEdge(hisBin))*0.5)
if testMbb_rMCa_2jets.GetBinContent(hisBin)+histMbb_MCb_2jets.GetBinError(hisBin)!=0:
n_ey.append(math.sqrt(pow(histMbb_MCb_2jets.GetBinError(hisBin),2)+pow(testMbb_rMCa_2jets.GetBinError(hisBin),2))/(histMbb_MCb_2jets.GetBinContent(hisBin)+testMbb_rMCa_2jets.GetBinContent(hisBin)))
else:
n_ey.append(2)
gr = TGraphErrors(binNum,np.array(n_x, dtype=float),np.array(n_y, dtype=float),np.array(n_ex, dtype=float),np.array(n_ey, dtype=float))
gr.GetXaxis().SetLimits(minElem,maxElem)
gr.GetYaxis().CenterTitle(1)
gr.GetYaxis().SetTitleOffset(0.3)
gr.GetYaxis().SetTitleSize(0.1)
gr.GetXaxis().SetTitle(obs_axis[obs_idx])
gr.GetXaxis().SetTitleOffset(0.55)#0.25
gr.GetXaxis().SetTitleSize(0.10)
gr.GetYaxis().SetLabelSize(0.02)
gr.GetXaxis().SetLabelSize(0.04)
gr.SetMarkerStyle(1)
gr.SetFillColorAlpha(ROOT.kPink+6, 0.25)
gr.SetLineColor(ROOT.kPink+6)
gr.GetYaxis().SetTitle("w.r.t MGPy8")
gr.GetYaxis().SetRangeUser(0.5,1.5)
legend.AddEntry(gr, "(Test+MCb)Stat Unc.")
legend.SetTextSize(0.045)
legend.Draw()
can2.cd()
ratioPad_2.Draw()
ratioPad_2.cd()
gr.Draw("a2")
line = TLine(0,1,maxElem,1)
line.SetLineWidth(2)
line.SetLineStyle(2)
line.Draw("SAME")
ratio_baseline = histMbb_MCa_2jets.Clone("ratio_hista")
ratio_baseline.Divide(histMbb_MCb_2jets)
ratio_baseline.SetFillColorAlpha(0, 0.25)
ratio_baseline.SetMarkerStyle(86)
ratio_baseline.SetMarkerColor(ROOT.kAzure+7)
ratio_baseline.SetMarkerSize(0.7)
ratio_baseline2 = testMbb_rMCa_2jets.Clone("ratio_histr_test")
ratio_baseline2.Divide(histMbb_MCb_2jets)
ratio_baseline2.SetMarkerColor(ROOT.kBlue)
ratio_baseline2.SetMarkerSize(0.7)
ratio_baseline2.GetYaxis().SetRangeUser(0.5,1.5)
ratio_baseline2.GetYaxis().CenterTitle(1)
ratio_baseline2.GetYaxis().SetTitleOffset(0.5)
ratio_baseline2.GetYaxis().SetTitle("w.r.t MGPy8")
ratio_baseline2.GetYaxis().SetTitleSize(0.1)
ratio_baseline2.GetXaxis().SetTitle(obs_axis[obs_idx])
ratio_baseline2.GetXaxis().SetTitleOffset(0.25)
ratio_baseline2.GetXaxis().SetTitleSize(0.1)
ratio_baseline2.GetYaxis().SetLabelSize(0.04)
ratio_baseline2.Draw("hist p SAME")
ratio_baseline.Draw("hist p SAME")
myfile2 = TFile('h_'+obs[obs_idx]+'_2jets_jflav_test7.root', 'RECREATE')
ratio_baseline.Write()
ratio_baseline2.Write()
myfile2.Close()
can2.cd()
can2.Draw()
can2.Update()
can2.SaveAs("Spec/Obs_"+obs[obs_idx]+"_2jets_Demo.png")
can2.Close()
can3 = TCanvas("mBB_3jet","mBB")
mainPad_3 = TPad("mainPad_3", "top_3", 0.02, 0.45, 0.98,0.98)
ratioPad_3 = TPad("ratioPad_3","bottom_3", 0.02, 0.08, 0.98, 0.45)
mainPad_3.SetBottomMargin(0.01)
ratioPad_3.SetTopMargin(0.08)
ratioPad_3.SetBottomMargin(0.15)
#mainPad_3.SetLogy()
mainPad_3.Draw()
mainPad_3.cd()
histMbb_MCa_3jets.GetYaxis().SetTitle("#frac{d#sigma}{d"+obs[obs_idx]+"}")
histMbb_MCa_3jets.SetFillColorAlpha(ROOT.kAzure+7, 0.25)
histMbb_MCa_3jets.SetLineColor(ROOT.kAzure+7)
histMbb_MCa_3jets.GetYaxis().SetTitleSize(0.04)
histMbb_MCa_3jets.GetYaxis().SetLabelSize(0.02)
histMbb_MCa_3jets.GetXaxis().SetLabelSize(0.02)
histMbb_MCa_3jets.GetYaxis().SetTitleOffset(0.7)
histMbb_MCa_3jets.GetXaxis().SetTitleOffset(0.4)
histMbb_MCa_3jets.DrawCopy("hist")
histMbb_MCb_3jets.GetYaxis().SetTitle("#frac{d#sigma}{d"+obs[obs_idx]+"}")
histMbb_MCb_3jets.SetFillColorAlpha(ROOT.kOrange-3, 0.25)
histMbb_MCb_3jets.SetLineColor(ROOT.kOrange-3)
histMbb_MCb_3jets.GetYaxis().SetTitleSize(0.04)
histMbb_MCb_3jets.GetYaxis().SetLabelSize(0.02)
histMbb_MCb_3jets.GetXaxis().SetLabelSize(0.02)
histMbb_MCb_3jets.GetYaxis().SetTitleOffset(0.7)
histMbb_MCb_3jets.DrawCopy("hist SAME")
testMbb_rMCa_3jets.SetFillColorAlpha(ROOT.kBlue, 0.25)
testMbb_rMCa_3jets.SetLineColor(ROOT.kBlue)
testMbb_rMCa_3jets.GetYaxis().SetTitleSize(0.04)
testMbb_rMCa_3jets.GetYaxis().SetLabelSize(0.02)
testMbb_rMCa_3jets.GetXaxis().SetLabelSize(0.02)
testMbb_rMCa_3jets.DrawCopy("hist SAME")
tt1 = ROOT.TLatex()
tt1.SetNDC()
tt1.SetTextSize(0.055)
tt1.DrawLatex(0.35 ,0.75 ,"p-value(test, MCb):"+str(format(testMbb_rMCa_3jets.Chi2Test(histMbb_MCb_3jets,"WW P"),'.1E')))
tt3 = ROOT.TLatex()
tt3.SetNDC()
tt3.SetTextSize(0.055)
tt3.DrawLatex(0.35 ,0.65 ,"p-value(MCa, MCb):"+str(format(histMbb_MCa_3jets.Chi2Test(histMbb_MCb_3jets,"WW P"),'.1E')))
legend = TLegend(0.64,0.65,0.95,0.85)
legend.SetBorderSize(0)
legend.AddEntry(histMbb_MCb_3jets, "MGPy8 (3jets)", "l")
legend.AddEntry(histMbb_MCa_3jets, "Sherpa (3jets)", "l")
legend.AddEntry(testMbb_rMCa_3jets, "Sherpa(testing_3jets) * NN", "l")
#legend.AddEntry(trainMbb_rMCa, "MCa(training) * NN", "l")
n_ex=[]
n_ey=[]
n_x=[]
n_y=[]
for hisBin in range(histMbb_MCa_3jets.GetNbinsX()+1):
if hisBin ==0: continue
#print("histMbb_MCa_3jets.GetBinLowEdge(hisBin):{}".format(histMbb_MCa_3jets.GetBinLowEdge(hisBin)))
n_x.append(histMbb_MCa_3jets.GetBinLowEdge(hisBin)+ 0.5*(histMbb_MCa_3jets.GetBinLowEdge(hisBin+1)-(histMbb_MCa_3jets.GetBinLowEdge(hisBin))))
n_y.append(1) #center at 1 in the y-axis
n_ex.append((histMbb_MCa_3jets.GetBinLowEdge(hisBin+1)-histMbb_MCa_3jets.GetBinLowEdge(hisBin))*0.5)
if testMbb_rMCa_3jets.GetBinContent(hisBin)+histMbb_MCb_3jets.GetBinError(hisBin)!=0:
n_ey.append(math.sqrt(pow(histMbb_MCb_3jets.GetBinError(hisBin),2)+pow(testMbb_rMCa_3jets.GetBinError(hisBin),2))/(histMbb_MCb_3jets.GetBinContent(hisBin)+testMbb_rMCa_3jets.GetBinContent(hisBin)))
else:
n_ey.append(2)
gr = TGraphErrors(binNum,np.array(n_x, dtype=float),np.array(n_y, dtype=float),np.array(n_ex, dtype=float),np.array(n_ey, dtype=float))
gr.GetXaxis().SetLimits(minElem,maxElem)
gr.GetYaxis().CenterTitle(1)
gr.GetYaxis().SetTitleOffset(0.3)
gr.GetYaxis().SetTitleSize(0.1)
gr.GetXaxis().SetTitle(obs_axis[obs_idx])
gr.GetXaxis().SetTitleOffset(0.55)#0.25
gr.GetXaxis().SetTitleSize(0.10)
gr.GetYaxis().SetLabelSize(0.02)
gr.GetXaxis().SetLabelSize(0.04)
gr.SetMarkerStyle(1)
gr.SetFillColorAlpha(ROOT.kPink+6, 0.25)
gr.SetLineColor(ROOT.kPink+6)
gr.GetYaxis().SetTitle("w.r.t MGPy8")
gr.GetYaxis().SetRangeUser(0.5,1.5)
legend.AddEntry(gr, "(Test+MCb)Stat Unc.")
legend.SetTextSize(0.045)
legend.Draw()
can3.cd()
ratioPad_3.Draw()
ratioPad_3.cd()
gr.Draw("a2")
line = TLine(0,1,maxElem,1)
line.SetLineWidth(2)
line.SetLineStyle(2)
line.Draw("SAME")
ratio_baseline = histMbb_MCa_3jets.Clone("ratio_hista")
ratio_baseline.Divide(histMbb_MCb_3jets)
ratio_baseline.SetFillColorAlpha(0, 0.25)
ratio_baseline.SetMarkerStyle(86)
ratio_baseline.SetMarkerColor(ROOT.kAzure+7)
ratio_baseline.SetMarkerSize(0.7)
ratio_baseline2 = testMbb_rMCa_3jets.Clone("ratio_histr_test")
ratio_baseline2.Divide(histMbb_MCb_3jets)
ratio_baseline2.SetMarkerColor(ROOT.kBlue)
ratio_baseline2.SetMarkerSize(0.7)
ratio_baseline2.GetYaxis().SetRangeUser(0.5,1.5)
ratio_baseline2.GetYaxis().CenterTitle(1)
ratio_baseline2.GetYaxis().SetTitleOffset(0.5)
ratio_baseline2.GetYaxis().SetTitle("w.r.t MGPy8")
ratio_baseline2.GetYaxis().SetTitleSize(0.1)
ratio_baseline2.GetXaxis().SetTitle(obs_axis[obs_idx])
ratio_baseline2.GetXaxis().SetTitleOffset(0.25)
ratio_baseline2.GetXaxis().SetTitleSize(0.1)
ratio_baseline2.GetYaxis().SetLabelSize(0.04)
ratio_baseline2.Draw("hist p SAME")
ratio_baseline.Draw("hist p SAME")
myfile3 = TFile('h_'+obs[obs_idx]+'_3jets_jflav_test7.root', 'RECREATE')
ratio_baseline.Write()
ratio_baseline2.Write()
myfile3.Close()
can3.cd()
can3.Draw()
can3.Update()
can3.SaveAs("Spec/Obs_"+obs[obs_idx]+"_3jets_Demo.png")
can3.Close()