Installation

This project is developed using Julia.

For ease of use and to maximize reproducibility we also provide container images using Singularity.

Source code

The fastest and easiest way is to clone the repository using Git. Alternatively you can download zipped releases. The below assumes you have Julia 1.9 or higher installed.

In an empty, new folder:

git clone https://github.com/bcardoen/SubPrecisionContactDetection.jl.git
cd SubPrecisionContactDetection.jl
julia --project=. -e `using Pkg; Pkg.build(); Pkg.test()`

This downloads the source code in a subfolder, builds it with all dependencies and tests it.

Once you have this, you can use either a terminal or an IDE (e.g. Visual Studio Code) to work with the source code to process new datasets. We recommend VSCode + the Julia Plugin for easy of use.

Updating

If you want to get the latest version, using git do:

git pull origin main

Then make sure everything still works

julia --project=. -e 'using Pkg; Pkg.build();Pkg.test();`

This assumes you did not switch brances or modified the code.

Singularity/Apptainer

We provide a preconfigured container image with all dependencies here.

Dependencies

All dependencies are automatically installed, however, you may run into issues if you have a non-standard Python installation. See the build script for details, but when in doubt, set the environment variable PYTHON to either your Python installation or the empty string and rebuild

export PYTHON=""
julia --project=. -e 'using Pkg; Pkg.build()'

Python dependencies

The postprocessing script uses dependencies that can be installed by issuing this command:

pip install kneed scikit-image scipy pandas argparse scikit-learn