This course is inspired in part by the text From Statistical Physics to Data-Driven Modelling, by Cocco, Monasson, and Zamponi, as well as the accompanying tutorials provided by the authors.

The following is a tentative outline of the course and is subject to change.

• This repository.
• Course textbook and tutorials.

On your computer, use the command line to navigate to wherever you would like to keep this repository. Then, clone this repository as follows.

cd <path/to/my/repos>
git clone https://github.com/AddisonHowe/phys2ddm.git
cd phys2ddm

You should now have a copy of the course repository, which you can edit freely. As this course is a work in progress, you will likely need to update this repository periodically, as we add additional content. To do so, you can simply run the command git pull from within the phys2ddm directory.

Most of the course content will involve python programming. We recommend using conda to manage python environments and install the necessary packages. If you don't already have conda installed, you can install it by following the directions for your operating system here. We recommend installing the miniconda distribution.

Once conda is installed, you can use it to create individual Python environments. The line below will create a new environment, called p2ddm-env, and install a handful of packages.

conda create -n p2ddm-env python=3.10 numpy scipy matplotlib pandas seaborn bokeh jupyter ipykernel watermark

Activate the new environment by running

conda activate p2ddm-env

Test that things are working properly by running the following line

python -c "import numpy; print('Success!')"

The tutorials for the course will be in the form of Jupyter Notebooks. By installing jupyter in your conda environment (see above), you should be able to start a Jupyter session with the command

jupyter notebook </path/to/directory/>

You may also choose to use another IDE, such as PyCharm or VS Code.

For questions or comments, please feel free to contact us.

1. Cocco S, Monasson R, Zamponi F. From Statistical Physics to Data-Driven Modelling: with Applications to Quantitative Biology [Internet]. 1st ed. Oxford University PressOxford; 2022 [cited 2024 Mar 7]. Available from: https://academic.oup.com/book/44725

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