From c276894d20e705f8d20e0d32ceebf62dacbcf559 Mon Sep 17 00:00:00 2001
From: Olivier Couet <olivier.couet@cern.ch>
Date: Wed, 22 Jun 2016 13:20:19 +0200
Subject: [PATCH] - Apply patches suggested by Mattias Ellert - Simplify the
reference to the example.
---
hist/hist/src/THnSparse.cxx | 5 ++---
1 file changed, 2 insertions(+), 3 deletions(-)
diff --git a/hist/hist/src/THnSparse.cxx b/hist/hist/src/THnSparse.cxx
index d6b9e6349e3..34412cf4dbd 100644
--- a/hist/hist/src/THnSparse.cxx
+++ b/hist/hist/src/THnSparse.cxx
@@ -544,7 +544,7 @@ with linear index linidx. A possible call would be
## Efficiency
TH1 and TH2 are generally faster than THnSparse for one and two dimensional
distributions. THnSparse becomes competitive for a sparsely filled TH3
-with large numbers of bins per dimension. The tutorial hist/sparsehist.C
+with large numbers of bins per dimension. The tutorial sparsehist.C
shows the turning point. On a AMD64 with 8GB memory, THnSparse "wins"
starting with a TH3 with 30 bins per dimension. Using a THnSparse for a
one-dimensional histogram is only reasonable if it has a huge number of bins.
@@ -765,8 +765,7 @@ Double_t THnSparse::GetBinContent(Long64_t idx, Int_t* coord /* = 0 */) const
////////////////////////////////////////////////////////////////////////////////
/// Get square of the error of bin addressed by linidx as
-/// BEGIN_LATEX #sum weight^{2}
-/// END_LATEX
+/// \f$\sum weight^{2}\f$
/// If errors are not enabled (via Sumw2() or CalculateErrors())
/// return contents.
--
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