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https://github.com/drvinceknight/Nashpy

A python library for 2 player games.
https://github.com/drvinceknight/Nashpy

algorithm computer-science equilibria game mathematics nash python

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A python library for 2 player games.

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# Nashpy: a python library for 2 player games.



Nashpy is:



- An [excellently documented library](https://nashpy.readthedocs.io/en/stable/):

  - The [Nashpy game theory text book](https://nashpy.readthedocs.io/en/stable/text-book/index.html) aims

    to be a course text on the background theory.

  - The [contributor

    documentation](https://nashpy.readthedocs.io/en/stable/contributing/index.html)

    aims to be a text on research software development and help **first time** open

    source software contributions.

- A [state of the art developed code

  base](https://nashpy.readthedocs.io/en/stable/contributing/index.html) which

  aims to use the best of available tools to ensure the code is correct,

  readable and robust.

- Feature rich, the following are implemented:

  - Support enumeration [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/solve-with-support-enumeration.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/support-enumeration.html)

  - Vertex enumeration [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/solve-with-vertex-enumeration.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/vertex-enumeration.html)

  - Lemke-Howson algorithm [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/solve-with-lemke-howson.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/lemke-howson.html)

  - Fictitious play [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-fictitious-play.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/fictitious-play.html)

  - Stochastic fictitious play [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-stochastic-fictitious-play.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/stochastic-fictitious-play.html)

  - Replicator dynamics [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-replicator-dynamics.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/replicator-dynamics.html)

  - Replicator-mutation dynamics [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-replicator-dynamics-with-mutation.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/replicator-dynamics.html#the-replicator-mutation-dynamics-equation)

  - Asymmetric replicator dynamics [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-asymmetric-replicator-dynamics.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/asymmetric-replicator-dynamics.html)

  - Moran processes [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-moran-processes.html)

  - Generate games from repeated games [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/obtain-a-repeated-game.html) - [Theory docs 📘](https://nashpy.readthedocs.io/en/stable/text-book/repeated-games.html)

  - Moran processes on interaction graphs [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-moran-process-on-interaction-graph.html)

  - Moran processes on replication graphs [How to docs 🐍](https://nashpy.readthedocs.io/en/stable/how-to/use-moran-process-on-replication-graph.html)



## Documentation



Full documentation is available here: http://nashpy.readthedocs.io/



## Installation



```bash

$ python -m pip install nashpy

```



To install Nashpy on Fedora, use:



```sh

$ dnf install python3-nashpy

```



## Usage



Create bi matrix games by passing two 2 dimensional arrays/lists:



```python

>>> import nashpy as nash

>>> A = [[1, 2], [3, 0]]

>>> B = [[0, 2], [3, 1]]

>>> game = nash.Game(A, B)

>>> for eq in game.support_enumeration():

...     print(eq)

(array([1., 0.]), array([0., 1.]))

(array([0., 1.]), array([1., 0.]))

(array([0.5, 0.5]), array([0.5, 0.5]))

>>> game[[0, 1], [1, 0]]

array([3, 3])



```



## Other game theoretic software



- [Gambit](http://www.gambit-project.org/) is a library with a python api and

  support for more algorithms and more than 2 player games.

- [Game theory explorer](http://gte.csc.liv.ac.uk/index/) a web interface to

  gambit useful for teaching.

- [Axelrod](http://axelrod.readthedocs.io/en/stable/) a research library aimed

  at the study of the Iterated Prisoners dilemma



## Development



Clone the repository and create a virtual environment:



```bash

$ git clone https://github.com/drvinceknight/nashpy.git

$ cd nashpy

$ python -m venv env



```



Activate the virtual environment and install [`tox`](https://tox.readthedocs.io/en/latest/):



```bash

$ source env/bin/activate

$ python -m pip install tox



```



Make modifications.



To run the tests:



```bash

$ python -m tox



```



To build the documentation. First install the software which also installs the

documentation build requirements.



```bash

$ python -m pip install flit

$ python -m flit install --symlink

```



Then:



```bash

$ cd docs

$ make html

```



Full contribution documentation is available at

https://nashpy.readthedocs.io/en/latest/contributing/index.html



Pull requests are welcome.



## Code of conduct



In the interest of fostering an open and welcoming environment, all

contributors, maintainers and users are expected to abide by the Python code of

conduct: https://www.python.org/psf/codeofconduct/