rf711_lagrangianmorph.py

## \ingroup tutorial_roofit_main

## \notebook -js

## Morphing effective field theory distributions with RooLagrangianMorphFunc.

## A morphing function as a function of one coefficient is setup and can be used

## to obtain the distribution for any value of the coefficient.

##

## \macro_image

## \macro_code

## \macro_output

##

## \date January 2022

## \author Rahul Balasubramanian

import ROOT

ROOT.gStyle.SetOptStat(0)

ROOT.PyConfig.IgnoreCommandLineOptions = True

ROOT.gROOT.SetBatch(True)

# Create functions

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

observablename = "pTV"

# Setup observable that is to be morphed

obsvar = ROOT.RooRealVar(observablename, "p_{T}^{V}", 10, 600)

# Setup two couplings that enters the morphing function

# kSM -> SM coupling set to constant (1)

# cHq3 -> EFT parameter with NewPhysics attribute set to true

kSM = ROOT.RooRealVar("kSM", "sm modifier", 1.0)

cHq3 = ROOT.RooRealVar("cHq3", "EFT modifier", 0.0, 1.0)

cHq3.setAttribute("NewPhysics", True)

# Inputs to setup config

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

infilename = ROOT.gROOT.GetTutorialDir().Data() + "/roofit/roofit/input_histos_rf_lagrangianmorph.root"

par = "cHq3"

samplelist = ["SM_NPsq0", "cHq3_NPsq1", "cHq3_NPsq2"]

# Set Config

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

config = ROOT.RooLagrangianMorphFunc.Config()

config.fileName = infilename

config.observableName = observablename

config.folderNames = samplelist

config.couplings.add(cHq3)

config.couplings.add(kSM)

# Create morphing function

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

morphfunc = ROOT.RooLagrangianMorphFunc("morphfunc", "morphed dist. of pTV", config)

# Get morphed distribution at cHq3 = 0.01, 0.5

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

morphfunc.setParameter("cHq3", 0.01)

morph_hist_0p01 = morphfunc.createTH1("morph_cHq3=0.01")

morphfunc.setParameter("cHq3", 0.25)

morph_hist_0p25 = morphfunc.createTH1("morph_cHq3=0.25")

morphfunc.setParameter("cHq3", 0.5)

morph_hist_0p5 = morphfunc.createTH1("morph_cHq3=0.5")

morph_datahist_0p01 = ROOT.RooDataHist("morph_dh_cHq3=0.01", "", [obsvar], morph_hist_0p01)

morph_datahist_0p25 = ROOT.RooDataHist("morph_dh_cHq3=0.25", "", [obsvar], morph_hist_0p25)

morph_datahist_0p5 = ROOT.RooDataHist("morph_dh_cHq3=0.5", "", [obsvar], morph_hist_0p5)

# Extract input templates for plotting

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

input_hists = {sample: ROOT.TFile.Open(infilename).Get(sample).FindObject(observablename) for sample in samplelist}

input_datahists = {

sample: ROOT.RooDataHist("dh_" + sample, "dh_" + sample, [obsvar], input_hists[sample]) for sample in samplelist

}

# Plot input templates

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

frame0 = obsvar.frame(Title="Input templates for p_{T}^{V}")

for sample, color in zip(samplelist, "krb"):

input_datahists[sample].plotOn(frame0, Name=sample, LineColor=color, MarkerColor=color, MarkerSize=1)

# Plot morphed templates for cHq3=0.01,0.25,0.5

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

frame1 = obsvar.frame(Title="Morphed templates for selected values")

plot_args = dict(

DrawOption="C",

DataError=None,

XErrorSize=0,

)

morph_datahist_0p01.plotOn(frame1, Name="morph_dh_cHq3=0.01", LineColor="kGreen", **plot_args)

morph_datahist_0p25.plotOn(frame1, Name="morph_dh_cHq3=0.25", LineColor="kGreen+1", **plot_args)

morph_datahist_0p5.plotOn(frame1, Name="morph_dh_cHq3=0.5", LineColor="kGreen+2", **plot_args)

# Create wrapped pdf to generate 2D dataset of cHq3 as a function of pTV

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

model = ROOT.RooWrapperPdf("wrap_pdf", "wrap_pdf", morphfunc)

data = model.generate({cHq3, obsvar}, 1000000)

hh_data = data.createHistogram("x,y", obsvar, Binning=20, YVar=dict(var=cHq3, Binning=50))

hh_data.SetTitle("Morphing prediction")

# Draw plots on canvas

# -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -

c1 = ROOT.TCanvas("fig3", "fig3", 1200, 400)

c1.Divide(3, 1)

c1.cd(1)

ROOT.gPad.SetLeftMargin(0.15)

ROOT.gPad.SetRightMargin(0.05)

frame0.Draw()

leg1 = ROOT.TLegend(0.55, 0.65, 0.94, 0.87)

leg1.SetTextSize(0.04)

leg1.SetFillColor("background")

leg1.SetLineColor("background")

leg1.AddEntry("SM_NPsq0", "SM", "LP")

leg1.AddEntry(0, "", "")

leg1.AddEntry("cHq3_NPsq1", "c_{Hq^{(3)}}=1.0 at #Lambda^{-2}", "LP")

leg1.AddEntry(0, "", "")

leg1.AddEntry("cHq3_NPsq2", "c_{Hq^{(3)}}=1.0 at #Lambda^{-4}", "LP")

leg1.Draw()

c1.cd(2)

ROOT.gPad.SetLeftMargin(0.15)

ROOT.gPad.SetRightMargin(0.05)

frame1.Draw()

leg2 = ROOT.TLegend(0.62, 0.65, 0.94, 0.87)

leg2.SetTextSize(0.04)

leg2.SetFillColor("w")

leg2.SetLineColor("w")

leg2.AddEntry("morph_dh_cHq3=0.01", "c_{Hq^{(3)}}=0.01", "L")

leg2.AddEntry(0, "", "")

leg2.AddEntry("morph_dh_cHq3=0.25", "c_{Hq^{(3)}}=0.25", "L")

leg2.AddEntry(0, "", "")

leg2.AddEntry("morph_dh_cHq3=0.5", "c_{Hq^{(3)}}=0.5", "L")

leg2.AddEntry(0, "", "")

leg2.Draw()

c1.cd(3)

ROOT.gPad.SetLeftMargin(0.12)

ROOT.gPad.SetRightMargin(0.18)

ROOT.gStyle.SetNumberContours(255)

ROOT.gStyle.SetPalette(ROOT.kGreyScale)

ROOT.gStyle.SetOptStat(0)

ROOT.TColor.InvertPalette()

ROOT.gPad.SetLogz()

hh_data.GetYaxis().SetTitle("c_{Hq^{(3)}}")

hh_data.GetYaxis().SetRangeUser(0, 0.5)

hh_data.GetZaxis().SetTitleOffset(1.8)

hh_data.Draw("COLZ")

c1.SaveAs("rf711_lagrangianmorph.png")