.. _visualising-results:

Visualising results
===================

This tutorial will show you briefly how to visualise some basic results

Visualising the results of the tournament
-----------------------------------------

As shown in :ref:`creating_tournaments`, let us create a tournament, but this
time we will include a player that acts randomly::

    >>> import axelrod as axl
    >>> players = [axl.Cooperator(), axl.Defector(),
    ...            axl.TitForTat(), axl.Grudger()]
    >>> players.append(axl.Random())
    >>> tournament = axl.Tournament(players)
    >>> results = tournament.play()

We can view these results (which helps visualise the stochastic effects)::

    >>> plot = axl.Plot(results)
    >>> p = plot.boxplot()
    >>> p.show()

.. image:: _static/visualising_results/demo_strategies_boxplot.svg
   :width: 50%
   :align: center

Visualising the distributions of wins
-------------------------------------

We can view the distributions of wins for each strategy::

    >>> p = plot.winplot()
    >>> p.show()

.. image:: _static/visualising_results/demo_strategies_winplot.svg
   :width: 50%
   :align: center

Visualising the payoff matrix
-----------------------------

We can also easily view the payoff matrix described in
:ref:`tournament-results`, this becomes particularly useful when viewing the
outputs of tournaments with a large number of strategies::

    >>> p = plot.payoff()
    >>> p.show()

.. image:: _static/visualising_results/demo_strategies_payoff.svg
   :width: 50%
   :align: center

Saving all plots
----------------

The :code:`axelrod.Plot` class has a method: :code:`save_all_plots` that will
save all the above plots to file.

Passing various objects to plot
-------------------------------

The library give access to underlying matplotlib axes objects of each plot, thus
the user can easily modify various aspects of a plot::

    >>> import matplotlib.pyplot as plt
    >>> _, ax = plt.subplots()
    >>> title = ax.set_title('Payoff')
    >>> xlabel = ax.set_xlabel('Strategies')
    >>> p = plot.boxplot(ax=ax)
    >>> p.show()

.. image:: _static/visualising_results/title_labels_payoff.png
   :width: 50%
   :align: center