RAMP starting kit for the Acrobot challenge

Getting started

The starting kit requires Python 3.7 and the following packages:

• numpy
• scipy
• scikit-learn
• pandas
• xarray
• jupyter
• pytorch
• matplotlib
• altair (see below to install this package as you need to install specific dependencies)
• ramp-workflow (see below to install this package as you will need a specific version)

Python 3.7 and all these packages (except altair and ramp-workflow) can be easily installed using the Anaconda distribution.

altair installation

As we use altair in the starting kit notebook you need to install it with the required dependencies. This can be done using conda

conda install -c conda-forge altair vega_datasets notebook vega

or using pip

pip install -U altair vega_datasets notebook vega

You can refer to the altair installation documentation for more information.

ramp-workflow installation

For the purpose of this challenge we need to install a specific branch of ramp-workflow. This can be done using pip

pip install git+https://github.com/paris-saclay-cds/ramp-workflow.git@generative_regression_clean

An alternative solution is to clone the ramp-workflow repository by running

git clone https://github.com/paris-saclay-cds/ramp-workflow.git

(you can use SSH instead of HTTPS). Then cd to the ramp-workflow folder and run

git checkout -b generative_regression_clean
pip install .

Using the requirements.txt file

If you are using pip you can easily install all the required packages except pytorch with

pip install -r requirements.txt

To install pytorch you can follow the instructions available on the pytorch website.

Getting the starting kit

To get the starting kit with the notebook and the submission examples clone the acrobot repository.

git clone https://github.com/ramp-kits/acrobot

To run the notebook, cd to the acrobot folder and run

jupyter notebook acrobot_starting_kit.ipynb