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--- root:pyroot_ttree [2017/09/05 10:34] – [Handling TTree trees] iwn
+++ root:pyroot_ttree [2018/02/28 13:58] – [Looping over a TTree] iwn
@@ Line 3: / Line 3: @@
 ====== Handling TTree trees ======
-[[https://root.cern.ch/doc/master/classTTree.html|Here]] is the class manual for ''TTree''.
+[[https://root.cern.ch/doc/master/classTTree.html|Here]] is the class reference for ''TTree''.
 [[root:example_TTree|Here]] is one file containing multiple examples.
@@ Line 102: / Line 102: @@
 <code python>
 for event in tree:
-    print tree.px
+    print event.px
 </code>
 If you also need the event's index:
 <code python>
 for i, event in enumerate(tree):
-    print i, tree.px
+    print i, event.px
 </code>
 ===== Making a histogram with TTree =====
@@ Line 175: / Line 174: @@
 tree.Scan("run:lum:evt","pt1>30 && pt2>30")
 </code>
+===== TChain =====
+If you have a samples split into many files, each containing the same tree, you can either add the files into one big one in the command line with ''hadd'' or load them in a ''TChain'' in you analysis code.
+With ''hadd'' in the command line:
+<code bash>
+hadd sample.root sample_1.root sample_2.root sample_3.root
+</code>
+With ''TChain'':
+<code python>
+chain = TChain("tree_name")
+chain.Add("sample_1.root")
+chain.Add("sample_2.root")
+chain.Add("sample_3.root")
+for event in chain:
+  print event.px
+</code>
+Note it's also possible to use a glob wildcard: ''chain.Add("sample_*.root")''

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