df010_trivialDataSource.py

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## \file
## \ingroup tutorial_dataframe
## \notebook -draw
## Use the "trivial data source", an example data source implementation.
##
## This tutorial illustrates how use the RDataFrame in combination with a
## RDataSource. In this case we use a RTrivialDS, which is nothing more
## than a simple generator: it does not interface to any existing dataset.
## The RTrivialDS has a single column, col0, which has value n for entry n.
##
## Note that RTrivialDS is only a demo data source implementation and superior alternatives
## typically exist for production use (e.g. constructing an empty RDataFrame as `RDataFrame(nEntries)`).
##
## \macro_code
##
## \date September 2017
## \author Danilo Piparo (CERN)
 
import ROOT
 
# Create the data frame
MakeTrivialDataFrame = ROOT.RDF.MakeTrivialDataFrame
 
nEvents = 128
 
d_s = MakeTrivialDataFrame(nEvents)
 
# Now we have a regular RDataFrame: the ingestion of data is delegated to
# the RDataSource. At this point everything works as before.
h_s = d_s.Define("x", "1./(1. + col0)").Histo1D(("h_s", "h_s", 128, 0, .6), "x")
 
c = ROOT.TCanvas()
c.SetLogy()
h_s.Draw()
c.SaveAs("df010_trivialDataSource.png")
 
print("Saved figure to df010_trivialDataSource.png")