# Genex
> Genex makes it easy to write Genetic Algorithms with Elixir.
[](https://travis-ci.org/seanmor5/genex)
[](https://coveralls.io/github/seanmor5/genex?branch=master)
This library is inspired by Python's [DEAP](https://github.com/deap/deap).
## Installation
The package can be installed by adding `genex` to your list of dependencies in `mix.exs`.
```elixir
def deps do
[
{:genex, "~> 0.1.0"}
]
end
```
## Usage
Genex works by making transformations on a `Population`.
The simplest way to use Genex is by including it in one of your modules with default parameters.
It requires you to implement 3 functions: `encoding/0`, `fitness_function/1`, `terminate?/1`.
```elixir
defmodule OneMax do
use Genex
def encoding do
for _ <- 1..10, do: Enum.random(0..1)
end
def fitness_function(chromosome), do: Enum.sum(chromosome.genes)
def terminate?(population), do: population.max_fitness == 10
end
```
Your algorithm can then be run by calling the `run/0` method Genex provides.
## Visualization
Genex currently offers text visualization of populations. To view a summary of the solution your algorithm produced simply do:
```elixir
soln = OneMax.run()
Genex.Visualizers.Text.display_summary(soln)
```
## Genealogy
Genex comes with an implementation of a Genealogy tree using an Erlang digraph. The tree is available in the `history` field of the `Population` struct. As of this version of Genex, there are no pre-packaged genealogy visualizers. You'll have to find a third-party solution.
## Configuration
Genex can be configured like so:
```elixir
def MyGA do
use Genex, crossover_type: :two_point, crossover_rate: 0.5
...
end
```
Please see the [documentation](https://hexdocs.pm/genex/tutorials-getting-started.html#content) for a full list of configuration options.
