1
0
Fork 0
mirror of https://gitlab.rlp.net/mobitar/ReCo.jl.git synced 2024-11-08 22:21:08 +00:00
ReCo.jl/README.adoc
2022-01-24 22:07:39 +01:00

66 lines
No EOL
1.5 KiB
Text

= 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()
----