= ReCo.jl

image:https://img.shields.io/badge/code%20style-blue-4495d1.svg[Code Style: Blue, link=https://github.com/invenia/BlueStyle]

**Re**inforcement learning of **co**llective behavior.

== Setup

The steps from the setup have to be followed before running anything in the following sections.

=== Launch Julia

To activate the environment, navigate to the main directory `/ReCo.jl` and then run the following to launch Julia:

[source, bash]
----
cd ReCo.jl
julia --threads auto
----

`auto` automatically sets the number of threads to use. If you want to use a specific number `N` of threads, replace `auto` with `N`.

=== Acitivating environment

After launching Julia, the package environment has to be activated by running the follwing in the REPL:

[source, julia]
----
using Pkg
Pkg.activate(".")
----

=== Install dependencies
After activating the package environment, run the follwing to install the package dependencies:

[source, julia]
----
Pkg.instantiate()
----

== Run simulation
// TODO

== Run reinforcement learning
// TODO

== Run analysis

After running the following command blocks in the REPL, the output can be found in the directory `exports/graphics`.

=== Mean squared displacement

[source, julia]
----
include("analysis/mean_squared_displacement.jl")
run_msd_analysis()
run_random_walk()
----

=== Radial distribution function

[source, julia]
----
include("analysis/radial_distribution_function/radial_distribution_function.jl")
run_radial_distribution_analysis()
----