The Atomistic Cookbook¶
This cookbook contains recipes for atomic-scale modelling for materials and molecules, with a particular focus on machine learning and statistical sampling methods. Most of the examples rely heavily on software developed by the laboratory of computational science and modeling (COSMO, see its github page) but the cookbook is open for recipes using all types of modeling tools and techniques. Rather than focusing on the usage of a specific package, this cookbook provides concrete examples of the solution of modeling problems, often using a combination of several tools.
Downloading and running the recipes¶
Each recipe can be viewed online as an interactive HTML page, but
can also be downloaded as a stand-alone .py
script of
.ipynb
Jupyter notebook.
To simplify setting up an environment that contains all the dependencies
needed for each recipe, you can also download an environment.yml
file
that you can use with conda to create a custom environment to run the example.
# Pick a name for the environment and replace <environment-name> with it
conda env create --name <environment-name> --file environment.yml
# when you want to use the environment
conda env activate --name <environment-name>
Additional data needed for each example is usually either downloaded
dynamically, or can be found in a data
folder for each example,
or downloaded as a data.zip
file at the end of each recipe in
the website.
Table of contents¶
Recipe of the day¶
Want to try something new? Each day, one of the recipes in the cookbook is highlighted on the front page. There is one to suit everyone’s taste!