These are the humble beginnings of a generic and highly scalable platform for simulating digital twins using Markov chains.
Install the library using pip:
pip install git+https://github.com/Bovi-analytics/DigitalCowSimulationPlatform@mainOr add it to your requirements.txt file as a dependency:
chain-simulator @ git+https://github.com/Bovi-analytics/DigitalCowSimulationPlatform@main
This library is written in Python, specifically for Python 3.8 and newer. It is assumed that a supported Python interpreter is already installed. Dependency management is done using Hatch, make sure this tool is installed too. To set up your development environment, do the following:
- Clone the chain-simulator repository to your computer:
git clone https://github.com/Bovi-analytics/DigitalCowSimulationPlatform.git chain_simulator
- Move into the new folder named chain_simulator:
cd chain_simulator - Install all package dependencies in a virtual environment:
hatch env create
You should now be set up for contributing to the simulation platform!
This is the root of this Git repository. There are multiple folders and files to be found, below is a brief description of each in TOML-format:
[folders]
".github" = "Mostly GitHub Actions configurations to run tests on multiple operating systems"
changelog = "Small news files used for generating a changelog"
docs = "User guide and API documentation for the simulation platform"
src = "Source code of the simulation platform package"
tests = "Unit tests to test the simulation platform"
[files]
".gitignore" = "List of files and/or folders that must not be version-contolled"
".pre-commit-config.yml" = "Tasks to execute on each commit"
pyproject.toml = "Configurations for the build system, linters, type checkers and testing frameworks"
README.md = "Description of this repository"
tox.ini = "Configuration for Tox to run tests on multiple Python versions"Author: Max Nollet
Last updated: 22-06-2023