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Merge pull request #702 from drvinceknight/cleanrm
A minor clean up of the README
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README.rst

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A library with the following principles and goals:
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1. Enabling the reproduction of previous Iterated Prisoner's Dilemma research
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as easily as possible.
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as easily as possible.
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2. Creating the de-facto tool for future Iterated Prisoner's Dilemma
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research.
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research.
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3. Providing as simple a means as possible for anyone to define and contribute
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new and original Iterated Prisoner's Dilemma strategies.
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4. Emphasizing readability along with an open and welcoming community that
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is accommodating for developers and researchers of a variety of skill levels
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is accommodating for developers and researchers of a variety of skill levels.
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Currently the library contains well over 100 strategies and can perform a
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variety of tournament types (RoundRobin, Noisy, Spatially-distributed, and
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probabilistically ending) and population dynamics while taking advantage
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of multi-core processors.
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**Please contribute via pull request (or just get in touch with us).**
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For an overview of how to use and contribute to this repository, see the
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The full documentation can be found here:
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`axelrod.readthedocs.org/ <http://axelrod.readthedocs.org/>`__.
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The documentation includes details of how to setup a tournament but here is an
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example showing how to create a tournament with all stochastic strategies::
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import axelrod
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strategies = [s() for s in axelrod.ordinary_strategies if s().classifier['stochastic']]
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tournament = axelrod.Tournament(strategies)
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results = tournament.play()
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The :code:`results` object now contains all the results we could need::
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The documentation includes details of how to setup a tournament but here is a
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brief example showing how to get a simple tournament::
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print(results.ranked_names)
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>>> import axelrod as axl
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>>> axl.seed(0) # Set a seed
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>>> players = [s() for s in axl.demo_strategies] # Create players
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>>> tournament = axl.Tournament(players) # Create a tournament
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>>> results = tournament.play() # Play the tournament
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>>> results.ranked_names
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['Defector', 'Grudger', 'Tit For Tat', 'Cooperator', 'Random: 0.5']
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gives::
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['Meta Hunter', 'Inverse', 'Forgetful Fool Me Once', 'GTFT: 0.33', 'Champion', 'ZD-GTFT-2', 'Eatherley', 'Math Constant Hunter', 'Random Hunter', 'Soft Joss: 0.9', 'Meta Majority', 'Nice Average Copier', 'Feld', 'Meta Minority', 'Grofman', 'Stochastic WSLS', 'ZD-Extort-2', 'Tullock', 'Joss: 0.9', 'Arrogant QLearner', 'Average Copier', 'Cautious QLearner', 'Hesitant QLearner', 'Risky QLearner', 'Random: 0.5', 'Meta Winner']
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There is also a `notebooks repository
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<https://github.com/Axelrod-Python/Axelrod-notebooks>`_ which shows further
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documentation:
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http://axelrod.readthedocs.org/en/latest/tutorials/contributing/index.html
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.. image:: https://graphs.waffle.io/Axelrod-Python/Axelrod/throughput.svg
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:target: https://waffle.io/Axelrod-Python/Axelrod/metrics
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:alt: 'Throughput Graph'
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Example notebooks
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=================
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doctests.py

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def load_tests(loader, tests, ignore):
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for root, dirs, files in os.walk("./docs"):
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for root, dirs, files in os.walk("."):
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for f in files:
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if f.endswith(".rst"):
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tests.addTests(

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