Analogous of TTreeReader for writing

Hi there,

now that the nice TTreeReader is available, is there an easy way to write only a subset of an input TTree (meaning only a few entries are retained)?


If you mean, you want to select certain events, then you can use TTree::CopyTree.
If you mean, copy only certain branches, then you can disable branches you don’t want to see in the new file:

auto inFile = TFile::Open("in.root");
auto tree = (TTree*) inFile->Get("tree_name");
// Disable all branches
tree->SetBranchStatus("*", kFALSE);
// Re-enable desired branches
tree->SetBranchStatus("mass", kTRUE);

auto newFile = new TFile("out.root", "recreate");
// Copy only those parts of the tree for which the selection string is true
// Note that any branch needed in the selection needs to be enabled (and will therefore also be copied)
auto newTree = tree->CopyTree("mass > 100");

If you want to add branches whose value depends on some of the old branches, have a look at my post about a function that accomplishes that: Add a new branch to a tree given only a formula

All of this will hopefully become way easier, as soon as ROOT 6.10 is published with its TDataFrame.


ROOT 6.10 is out:
As it was correctly stressed in the previous post, TDataFrame easily allows to:

  1. Select events (Filter transformation)
  2. Define new columns in the dataset (Define transformation)
  3. Save all or a few of the columns (branches) in a new tree (SnapShot action)

In a nutshell, supposed to have a tree with 2 branches, b1 and b2. Suppose you want to select some events according to some cut and you want to create an additional column. Suppose you want to save the result as a new dataset.

int MyMacro()
   // We prepare an input tree to run on
   auto fileName = "myinputfile.root";
   auto outFileName = "myoutputfile.root";
   auto treeName = "myTree";

   // We read the tree from the file and create a TDataFrame.
   ROOT::Experimental::TDataFrame d(treeName, fileName);

   // ## Select entries
   // We now select some entries in the dataset and save the intermediate TDataFrame
   auto d_cut = d.Filter("b1 % 2 == 0");
   // ## Enrich the dataset
   // Build some temporary columns: we'll write them out
   // One column is defined with a lambda, one with a jitted C++ string
   auto d2 = d_cut.Define("b1_square", "b1 * b1")
                              [](float b2) {
                                 std::vector<float> v;
                                 for (int i = 0; i < 3; i++) v.push_back(b2*i);
                                    return v;
   // ## Write it to disk in ROOT format
   // We now write to disk a new dataset with one of the variables originally
   // present in the tree and the new variables.
   // The user can explicitly specify the types of the columns as template
   // arguments of the Snapshot method, otherwise they will be automatically
   // inferred.
   d2.Snapshot(treeName, outFileName, {"b1", "b1_square", "b2_vector"});

All the tutorials can be found here:


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