df016_vecOps¶

Process collections in RDataFrame with the help of RVec.

This tutorial shows the potential of the VecOps approach for treating collections stored in datasets, a situation very common in HEP data analysis.

Author: Danilo Piparo (CERN)
This notebook tutorial was automatically generated with ROOTBOOK-izer from the macro found in the ROOT repository on Thursday, March 23, 2023 at 10:44 AM.

In [1]:

import ROOT

df = ROOT.RDataFrame(1024)
coordDefineCode = '''ROOT::RVecD {0}(len);
                     std::transform({0}.begin(), {0}.end(), {0}.begin(), [](double){{return gRandom->Uniform(-1.0, 1.0);}});
                     return {0};'''
d = df.Define("len", "gRandom->Uniform(0, 16)")\
      .Define("x", coordDefineCode.format("x"))\
      .Define("y", coordDefineCode.format("y"))

Welcome to JupyROOT 6.29/01

Now we have in our hands d, a RDataFrame with two columns, x and y, which hold collections of coordinates. The sizes of these collections vary. Let's now define radii radii from the x and y coordinates. We'll do it treating the collections stored in the columns without looping on the individual elements.

In [2]:

d1 = d.Define("r", "sqrt(x*x + y*y)")

Now we want to plot 2 quarters of a ring with radii .5 and 1. Note how the cuts are performed on RVecs, comparing them with integers and among themselves.

In [3]:

ring_h = d1.Define("rInFig", "r > .5 && r < 1 && x*y < 0")\
           .Define("yFig", "y[rInFig]")\
           .Define("xFig", "x[rInFig]")\
           .Histo2D(("fig", "Two quarters of a ring", 64, -1.1, 1.1, 64, -1.1, 1.1), "xFig", "yFig")

cring = ROOT.TCanvas()
ring_h.Draw("Colz")
cring.SaveAs("df016_ring.png")

print("Saved figure to df016_ring.png")

Saved figure to df016_ring.png

Info in <TCanvas::Print>: png file df016_ring.png has been created

Draw all canvases

In [4]:

from ROOT import gROOT 
gROOT.GetListOfCanvases().Draw()