From 57004c35577305e4a461d4b3d8b5311bee0d44a1 Mon Sep 17 00:00:00 2001
From: Jonathan Barnoud <jonathan@barnoud.net>
Date: Fri, 22 Jul 2016 17:49:31 +0200
Subject: [PATCH] Minor format changes in gbonc_autocorrel doc

---
 package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py b/package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py
index 463fb78dae9..31e4efabe1e 100644
--- a/package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py
+++ b/package/MDAnalysis/analysis/hbonds/hbond_autocorrel.py
@@ -32,7 +32,8 @@
 then the lifetime of these bonds is monitored over time.  Multiple passes
 through the trajectory are used to build an average of the behaviour.
 
-    :math:`C_x(t) = \\left \\langle \\frac{h_{ij}(t_0) h_{ij}(t_0 + t)}{h_{ij}(t_0)^2} \\right\\rangle`
+.. math::
+   C_x(t) = \\left \\langle \\frac{h_{ij}(t_0) h_{ij}(t_0 + t)}{h_{ij}(t_0)^2} \\right\\rangle
 
 The subscript :math:`x` refers to the definition of lifetime being used, either
 continuous or intermittent.  The continuous definition measures the time that
@@ -41,7 +42,8 @@
 be counted again.  The relevent lifetime, :math:`\\tau_x`, can then be found
 via integration of this function
 
-    :math:`\\tau_x = \\int_0^\\infty C_x(t) dt`
+.. math::
+   \\tau_x = \\int_0^\\infty C_x(t) dt`
 
 For this, the observed behaviour is fitted to a multi exponential function,
 using 2 exponents for the continuous lifetime and 3 for the intermittent
@@ -277,8 +279,8 @@ def _slice_traj(self, sample_time):
     def run(self, force=False):
         """Run all the required passes
 
-        Parameters:
-        -----------
+        Parameters
+        ----------
         force : bool, optional
             Will overwrite previous results if they exist
         """