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df003_profiles.py File Reference

Detailed Description

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Use TProfiles with RDataFrame.

This tutorial illustrates how to use TProfiles in combination with the RDataFrame. See the documentation of TProfile and TProfile2D to better understand the analogy of this code with the example one.

import ROOT
# A simple helper function to fill a test tree: this makes the example
# stand-alone.
def fill_tree(treeName, fileName):
d = ROOT.RDataFrame(25000)
d.Define("px", "gRandom->Gaus()")\
.Define("py", "gRandom->Gaus()")\
.Define("pz", "sqrt(px * px + py * py)")\
.Snapshot(treeName, fileName)
# We prepare an input tree to run on
fileName = "df003_profiles_py.root"
treeName = "myTree"
fill_tree(treeName, fileName)
# We read the tree from the file and create a RDataFrame.
d = ROOT.RDataFrame(treeName, fileName)
# Create the profiles
hprof1d = d.Profile1D(("hprof1d", "Profile of pz versus px", 64, -4, 4), "px", "py")
hprof2d = d.Profile2D(("hprof2d", "Profile of pz versus px and py", 40, -4, 4, 40, -4, 4, 0, 20), "px", "py", "pz")
# And Draw
c1 = ROOT.TCanvas("c1", "Profile histogram example", 200, 10, 700, 500)
hprof1d.Draw()
c1.SaveAs("df003_c1.png")
c2 = ROOT.TCanvas("c2", "Profile2D histogram example", 200, 10, 700, 500)
hprof2d.Draw()
c2.SaveAs("df003_c2.png")
print("Saved figures to df003_*.png")
ROOT's RDataFrame offers a modern, high-level interface for analysis of data stored in TTree ,...
Date
February 2017
Author
Danilo Piparo (CERN)

Definition in file df003_profiles.py.