freud library enables advanced analysis of particle simulations, particularly those utilizing periodic boundary conditions.
This collection of Jupyter notebooks provides examples of how the different modules of
freud can be used for different types of analysis.
These notebooks may be launched interactively on Binder or downloaded and run on your own system.
git clone https://github.com/glotzerlab/freud-examples.git cd freud-examples jupyter notebook # or "jupyter lab"
The recommended method for installing
freud is using conda (
conda install -c conda-forge freud) or pip (
pip install freud-analysis).
Refer to the Installation Guide for instructions to install from source.
jupyter labextension install jupyterlab_bokeh
If you have any issues with installing or seek more information about
freud, please refer to the
There are a few critical concepts, algorithms, and data structures that are central to all of
In order to familiarize yourself with these before delving too deep into the workings of specific
freud modules, we recommend looking through certain notebooks first.
In this cell and the next one, each
freud module is linked to the documentation for more information, while the links in the list point to Jupyter notebooks demonstrating the classes in those modules.
freud.box: The box module defines the Box object used throughout
freudto represent periodic simulation boxes. Since all analysis methods involve some representation of particles in a box of some sort, it is useful to understand boxes and periodicity before attempting to use the rest of
freud.locality: The locality module enables
NeighborListcalculations, which provide information on which particles are near to other particles in a system. These are described in the Reference documentation. Additional classes are demonstrated below.
These notebooks go into greater detail, showing the full functionality of each module in