Correction to the lines include in the symbreg example documentation.

--HG-- branch : dev
sumo2017 · May 14, 2013 · 566900e · 566900e
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diff --git a/doc/examples/gp_symbreg.rst b/doc/examples/gp_symbreg.rst
@@ -130,7 +130,7 @@ maximum of both the individuals fitness and size. For that we'll use a
 :class:`~deap.tools.MultiStatistics` object.
 
 	.. literalinclude:: /code/examples/gp/gp_symbreg.py
-	   :lines: 77-83
+	   :lines: 77-86
 
 Note that a simple :class:`~deap.tools.Statistics` object can be used, as in
 previous examples when statistics over a single key are desired.
@@ -144,13 +144,13 @@ creating the population and then calling a complete algorithm. In this case,
 we'll use :func:`~deap.algorithms.eaSimple`.
 
 .. literalinclude:: /code/examples/gp/gp_symbreg.py
-   :lines: 61, 73-87
+   :lines: 71,74,75,88-91
 
 
 The hall of fame is a specific structure which contains the *n* best
 individuals (here, the best one only).
 
-The complete example : [`source code <code/gp/gp_symbreg.py>`_].
+The complete [`source code <code/gp/gp_symbreg.py>`_].
 
 
 .. _refPapersSymbreg:

diff --git a/doc/releases.rst b/doc/releases.rst
@@ -6,6 +6,11 @@ Here is a (incomplete) log of the changes made to DEAP over time.
 To be released 1.0
 ==================
 
+- Changed the way statistics are handled and printed. See the
+  :class:`~deap.tools.Statistics` and :class:`~deap.tools.MultiStatistics`
+  documentation for more details.
+- Removed the EvolutionLogger, which functionalities are now handled by
+  by the ``__str__`` function of statistics objects.
 - Added object oriented inheritance to strongly typed genetic programming.
 - Added the possibility to name primitives added to a PrimitiveSet.
 - Added the pset to GP mutation operators that require it.

diff --git a/examples/gp/gp_symbreg.py b/examples/gp/gp_symbreg.py
@@ -85,7 +85,8 @@ def main():
     stats_fit.setColumns("avg", "max", "min", "std")
     stats_size.setColumns("avg", "max", "min", "std")
 
-    algorithms.eaSimple(pop, toolbox, 0.5, 0.1, 40, mstats, halloffame=hof, verbose=True)
+    algorithms.eaSimple(pop, toolbox, 0.5, 0.1, 40, stats=mstats,
+        halloffame=hof, verbose=True)
 
     return pop, mstats, hof