<commit_before># Nash: a python library for the computation of equilibria of 2 player strategic games.

**This is a library with simple dependencies (it only requires numpy) so that it
is pip installable: if you want to do sophisticated equilibria computation YOU
SHOULD use [gambit](https://github.com/gambitproject/gambit).**

This is a linear algebraic implementation of support enumeration using numpy.

This code is based on code that was implemented in
[Sagemath](http://www.sagemath.org/).

## Installation

The easiest way to install is from pypi:

```bash
$ pip install nashpy  # This doesn't work yet  #TODO Speak to James
```

## Usage

You can create a zero sum game by passing a single 2 dimensional array/list:

```python
>>> import nash
>>> A = [[1, -1], [-1, 1]]
>>> matching_pennies = nash.Game(A)
>>> matching_pennies.zero_sum
True

```<commit_msg>Slight reword of the README.<commit_after># Nash: a python library for the computation of equilibria of 2 player strategic games.

**This is a library with simple dependencies (it only requires numpy) so that it
is pip installable: if you want to do sophisticated equilibria computation YOU
SHOULD use [gambit](https://github.com/gambitproject/gambit).**

This is a linear algebraic implementation of support enumeration using numpy.

This algorithm has also been implemented in
[Sagemath](http://www.sagemath.org/).

## Installation

The easiest way to install is from pypi:

```bash
$ pip install nashpy  # This doesn't work yet  #TODO Speak to James
```

## Usage

You can create a zero sum game by passing a single 2 dimensional array/list:

```python
>>> import nash
>>> A = [[1, -1], [-1, 1]]
>>> matching_pennies = nash.Game(A)
>>> matching_pennies.zero_sum
True

```
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