Fixed some typo in the documentation

falconzyx · May 21, 2013 · 056fad8 · 056fad8
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diff --git a/doc/tutorials/gp.rst b/doc/tutorials/gp.rst
@@ -157,7 +157,7 @@ a terminal, ephemeral constant can also be typed
 Generation of Tree Individuals
 ------------------------------
 The code presented in the last two sections produce valid trees. 
-However, as in the :ref:`next-step` tutorial, these trees are yet valid
+However, as in the :ref:`next-step` tutorial, these trees are not yet valid
 individuals for evolution. One must combine the creator and the toolbox to
 produce valid individuals. We need to create the :class:`Fitness` and the
 :class:`Individual` classes. To the :class:`Individual`, in addition to the

diff --git a/doc/tutorials/next_step.rst b/doc/tutorials/next_step.rst
@@ -33,7 +33,7 @@ Evaluation
 ----------
 
 The evaluation is the most personal part of an evolutionary algorithm, it is
-the only part of the library that you must write your-self. A typical
+the only part of the library that you must write yourself. A typical
 evaluation function takes one individual as argument and return its fitness as
 a :class:`tuple`. As shown in the in the :ref:`core` section, a fitness is a list of floating point values and has a
 property :attr:`~deap.base.Fitness.valid` to know if this individual shall be re-evaluated. The

diff --git a/doc/tutorials/start.rst b/doc/tutorials/start.rst
@@ -1,6 +1,6 @@
 Where to Start?
 ===============
-If your are used to an other evolutionary algorithm framework, you'll notice
+If you are used to an other evolutionary algorithm framework, you'll notice
 we do things differently with DEAP. Instead of limiting you with predefined
 types, we provide ways of creating the appropriate ones. Instead of providing
 closed initializers, we enable you to customize them as you wish. Instead of

diff --git a/doc/tutorials/types.rst b/doc/tutorials/types.rst
@@ -210,7 +210,7 @@ that it is composed of lists of individuals.
 Calling :func:`toolbox.population` will readily return a complete population
 where the individuals are accessible using two indices for example
 ``pop[r][c]``. For the moment there is no algorithm specialized for structured
-population, we are waiting your submissions.
+population, we are waiting for your submissions.
 
 Swarm
 +++++