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--- root:pyroot_ttree [2017/06/27 13:23] – [Scanning a TTree] iwn
+++ root:pyroot_ttree [2018/02/28 14:03] (current) – [TChain] iwn
@@ Line 1: / Line 1: @@
+[[root:root|Getting started with ROOT]] -> [[root:pyroot|Useful pyROOT snippets]] → [[root:pyroot_ttree|Handling TTree trees]]
 ====== Handling TTree trees ======
+[[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 23: / Line 27: @@
 tree = TTree("tree_name", "tree title")
-# create 1 dimensional float arrays as fill variables, in this way the float array serves
+# create 1 dimensional float arrays as fill variables, in this way the float
-# as a pointer which can be passed to the branch
+# array serves as a pointer which can be passed to the branch
 px  = array('d',[0])
 phi = array('d',[0])
@@ Line 52: / Line 56: @@
 </code>
-Note that ''file.Write()'' will write all objects (trees, histograms, graphs, ...) that are still opened. Instead, you can write an object, in this case a ''TTree'', with the [[https://root.cern.ch/doc/master/classTTree.html#af6f2d9ae4048ad85fcae5d2afa05100f|Write() method]]:
+Note that ''file.Write()'' will write all objects (trees, histograms, graphs, ...) that are still opened. Instead, you can write a individual object, in this case a ''TTree'', with the [[https://root.cern.ch/doc/master/classTTree.html#af6f2d9ae4048ad85fcae5d2afa05100f|Write() method]]:
 <code python>
 tree.Write()
@@ Line 98: / 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 154: / Line 157: @@
-===== Scanning a TTree =====
+===== Scanning the values of a TTree =====
 Print the values of some branches in columns with ''TTree::Scan'':
@@ Line 160: / Line 163: @@
 tree.Scan("run:lumi:event")
 tree.Scan("run:lumi:event","pt1>30 && pt2>30") # with some selections
+tree.Scan("run:lumi:event","pt1>30 && pt2>30","colsize=8") # with some option
 </code>
-The [[https://root.cern.ch/doc/master/classTTreePlayer.html#aa0149b416e4b812a8762ec1e389ba2db|documentation of TTreePlayer::Scan()]] has more information on print options, formatting etc.
+The [[https://root.cern.ch/doc/master/classTTreePlayer.html#aa0149b416e4b812a8762ec1e389ba2db|documentation of TTreePlayer::Scan()]] has more information on print options (column size, decimal precision, ...) and formatting.
-To write the output directly to a file:
+To write the output directly to a file (which gets overwritten every time):
 <code python>
 tree.GetPlayer().SetScanRedirect(True)
@@ Line 170: / 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>
+Looping over the events in a chain is similar as for [[root:pyroot_ttree#looping_over_a_ttree|trees]]. Note it's also possible to use a glob wildcard: ''chain.Add("sample_*.root")''

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