imt101_parTreeProcessing.C

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/// \file
/// \ingroup tutorial_multicore
/// \notebook
/// Illustrate the usage of the TTreeProcessorMT::Process method.
/// Such method provides an implicit parallelisation of the reading and processing of a TTree.
/// In particular, when invoking Process, the user provides a function that iterates on a subrange
/// of the tree via a TTreeReader. Multiple tasks will be spawned, one for each sub-range, so that
/// the processing of the tree is parallelised. Since two invocations of the user function can
/// potentially run in parallel, the function code must be thread safe.
/// The example also introduces a new class, ROOT::TThreadedObject, which makes objects
/// thread private. With the help of this class, histograms can be filled safely inside the
/// user function and then merged at the end to get the final result.
///
/// \macro_code
///
/// \date 26/09/2016
/// \author Enric Tejedor

int imt101_parTreeProcessing()
{
   // First enable implicit multi-threading globally, so that the implicit parallelisation is on.
   // The parameter of the call specifies the number of threads to use.
   int nthreads = 4;
   ROOT::EnableImplicitMT(nthreads);

   // Create one TThreadedObject per histogram to fill during the processing of the tree
   ROOT::TThreadedObject<TH1F> ptHist("pt_dist", "p_{T} Distribution;p_{T};dN/p_{T}dp_{T}", 100, 0, 5);
   ROOT::TThreadedObject<TH1F> pzHist("pz_dist", "p_{Z} Distribution;p_{Z};dN/dp_{Z}", 100, 0, 5);
   ROOT::TThreadedObject<TH2F> pxpyHist("px_py", "p_{X} vs p_{Y} Distribution;p_{X};p_{Y}", 100, -5., 5., 100, -5., 5.);

   // Create a TTreeProcessorMT: specify the file and the tree in it
   ROOT::TTreeProcessorMT tp("http://root.cern.ch/files/tp_process_imt.root", "events");

   // Define the function that will process a subrange of the tree.
   // The function must receive only one parameter, a TTreeReader,
   // and it must be thread safe. To enforce the latter requirement,
   // TThreadedObject histograms will be used.
   auto myFunction = [&](TTreeReader &myReader) {
      TTreeReaderValue<std::vector<ROOT::Math::PxPyPzEVector>> tracksRV(myReader, "tracks");

      // For performance reasons, a copy of the pointer associated to this thread on the
      // stack is used
      auto myPtHist = ptHist.Get();
      auto myPzHist = pzHist.Get();
      auto myPxPyHist = pxpyHist.Get();

      while (myReader.Next()) {
         auto tracks = *tracksRV;
         for (auto &&track : tracks) {
            myPtHist->Fill(track.Pt(), 1. / track.Pt());
            myPxPyHist->Fill(track.Px(), track.Py());

            myPzHist->Fill(track.Pz());
         }
      }
   };

   // Launch the parallel processing of the tree
   tp.Process(myFunction);

   // Use the TThreadedObject::Merge method to merge the thread private histograms
   // into the final result
   auto ptHistMerged = ptHist.Merge();
   auto pzHistMerged = pzHist.Merge();
   auto pxpyHistMerged = pxpyHist.Merge();

   return 0;
}