TMVA_SOFIE_RDataFrame.py

### \ingroup tutorial_tmva

### \notebook -nodraw

### Example of inference with SOFIE and RDataFrame, of a model trained with Keras.

### First, generate the input model by running `TMVA_Higgs_Classification.C`.

###

### This tutorial parses the input model and runs the inference using ROOT's JITing capability.

###

### \macro_code

### \macro_output

### \author Lorenzo Moneta

import ROOT

from os.path import exists

ROOT.TMVA.PyMethodBase.PyInitialize()

# check if the input file exists

modelFile = "Higgs_trained_model.h5"

modelName = "Higgs_trained_model";

if not exists(modelFile):

raise FileNotFoundError("You need to run TMVA_Higgs_Classification.C to generate the Keras trained model")

# parse the input Keras model into RModel object

model = ROOT.TMVA.Experimental.SOFIE.PyKeras.Parse(modelFile)

# generating inference code

model.Generate()

model.OutputGenerated("Higgs_trained_model_generated.hxx")

model.PrintGenerated()

# compile using ROOT JIT trained model

print("compiling SOFIE model and functor....")

ROOT.gInterpreter.Declare('#include "Higgs_trained_model_generated.hxx"')

ROOT.gInterpreter.Declare('auto sofie_functor = TMVA::Experimental::SofieFunctor<7,TMVA_SOFIE_'+modelName+'::Session>(0,"Higgs_trained_model_generated.dat");')

# run inference over input data

inputFile = "http://root.cern/files/Higgs_data.root"

df1 = ROOT.RDataFrame("sig_tree", inputFile)

h1 = df1.Define("DNN_Value", "sofie_functor(rdfslot_,m_jj, m_jjj, m_lv, m_jlv, m_bb, m_wbb, m_wwbb)").Histo1D(("h_sig", "", 100, 0, 1),"DNN_Value")

df2 = ROOT.RDataFrame("bkg_tree", inputFile)

h2 = df2.Define("DNN_Value", "sofie_functor(rdfslot_,m_jj, m_jjj, m_lv, m_jlv, m_bb, m_wbb, m_wwbb)").Histo1D(("h_bkg", "", 100, 0, 1),"DNN_Value")

# run over the input data once, combining both RDataFrame graphs.

ROOT.RDF.RunGraphs([h1, h2]);

print("Number of signal entries",h1.GetEntries())

print("Number of background entries",h2.GetEntries())

h1.SetLineColor("kRed")

h2.SetLineColor("kBlue")

c1 = ROOT.TCanvas()

ROOT.gStyle.SetOptStat(0)

h2.DrawClone()

h1.DrawClone("SAME")