Documentation at: https://simula.github.io/damast
Firstly, you will want to create you an isolated development environment for Python, that being conda or venv-based. The following will go through a venv based setup.
Let us assume you operate with a 'workspace' directory for this project:
cd workspace
Here, you will create a virtual environment. Get an overview over venv (command):
python -m venv --help
Create your venv and activate it:
python -m venv damast-venv
source damast-venv/bin/activate
Clone the repo and install:
git clone https://github.com/simula/damast
cd damast
pip install -e ".[test,dev]"
or alternatively:
pip install damast[test,dev]
If you prefer to work or start with a docker container you can build it using the provided Dockerfile
docker build -t damast:latest -f Dockerfile .
To enter the container:
docker run -it --rm damast:latest /bin/bash
Once you installed the package you can locally generate the documentation:
tox -e build_docs
You can then open the documentation with a browser:
<yourbrowser> _build/html/index.html
Otherwise you will find API and usage documentation here.
Install the project and use the predefined default test environment:
tox -e py
This project is open to contributions. For details on how to contribute please check the Contribution Guidelines
This project is licensed under the BSD-3-Clause License.
Copyright (c) 2023-2025 Simula Research Laboratory, Oslo, Norway
This work has been derived from work that is part of the T-SAR project Some derived work is mainly part of the specific data processing for the 'maritime' domain.
The development of this library is part of the EU-project AI4COPSEC which receives funding from the Horizon Europe framework programme under Grant Agreement N. 101190021.