## \file

## \ingroup tutorial_dataframe

## \notebook -draw

## This tutorial shows how VecOps can be used to slim down the programming

## model typically adopted in HEP for analysis.

##

## \macro_code

## \macro_image

##

## \date March 2018

## \author Danilo Piparo, Andre Vieira Silva

import ROOT

from math import sqrt

filename = ROOT.gROOT.GetTutorialDir().Data() + "/dataframe/df017_vecOpsHEP.root"

treename = "myDataset"

RDF = ROOT.ROOT.RDataFrame

def WithPyROOT():

f = ROOT.TFile(filename)

h = ROOT.TH1F("pt", "pt", 16, 0, 4)

for event in f.myDataset:

for E, px, py in zip(event.E, event.px, event.py):

if (E > 100):

h.Fill(sqrt(px*px + py*py))

h.DrawCopy()

def WithRDataFrameVecOpsJit():

f = RDF(treename, filename)

h = f.Define("good_pt", "sqrt(px*px + py*py)[E>100]")\

.Histo1D(("pt", "pt", 16, 0, 4), "good_pt")

h.DrawCopy()

## We plot twice the same quantity, the key is to look into the implementation

## of the functions above

c = ROOT.TCanvas()

c.Divide(2,1)

c.cd(1)

WithPyROOT()

c.cd(2)

WithRDataFrameVecOpsJit()