Bryne is a Python framework to build coupled multiphysics FEM models. It also facilitates creating reproducible simulation setups by storing the full human-readable simulation setups with the results. The current implementation heavily leverages the DUNE-FEM Python API to set up models as FEM problems and solve them using just-in-time generated C++ code. This Zenodo record contains The repository code, archived at the present release version (versioned archive) A Docker container containing a compatible environment to reproduce tests and examples Documentation pages (under /documentation ) How to use the Docker image To reproduce the code at the state of the corresponding release version, the Zenodo record ships with a Docker container. The container can host a JupyterLab server to execute examples.The following examples require a working installation of Docker and a running Docker engine. Unix terminal commands (step-by-step instructions can be found at the end): tar -xvzf bryne_1.1.0.tar.gzdocker load -i bryne_docker_image.tar.gzexport BRYNE_DOCKER_IMAGE=registry.git.rwth-aachen.de/mbd/bryne/bryne:1.1.0tar -xf bryne_repo_1.1.0.tardocker run -w /root/shared --init -p 8888:8888 -v "$(pwd)":/root/shared $BRYNE_DOCKER_IMAGE Then, CTRL+Click on the lower URL appearing in the terminal, or copy it into a Browser to connect to the JupyterLab instance. How to reproduce examples and tests Open the bryne_repo/examples/how_to_use_jupyterlab.ipynb Notebook in the JupyterLab instance for visual instructions.Where can I find examples?Examples are located in the examples folder in the bryne_repo archive. More simulation setups are part of the pytest suite, located in the tests folder. How can I run the examples? The containerized JupyterLab instance is set up to allow quick reproduction of examples (bryne_repo/examples) and tests (bryne_repo/tests). To run a simulation, we have to navigate into a simulation folder and run the Python script that calls the Bryne driver, usually called run.py (or test_name_of_test.py for pytests). The easiest way is through JupyterLab. Connect to the JupyterLab server as described above, then open the desired simulation in the file browser on the right. You can right-click the run.py file in the file browser to execute the script through the GUI. Alternatively, you can use the included bash terminal to run simulations: python run.py How can I visualize the results?Simulation results for a specific model are stored in a directory named after the model in the output directory. The folder contains auxiliary information saved by the model and a Paraview folder with .vtk files. Note: VTK files might fail to load on outdated Paraview versions. We recommend version 5.12.0.Where can I find the FEM model source code?The actual implementation of models can be found in the /bryne/models/MODEL_NAME subdirectory of the code repo. There, you will usually find at least two Python modules. One implements the FEM model using the dune-fem API, and one defines model-specific parameters. ------------------------------------------- Step-by-step instructions: Download and extract the Zenodo record (version_number.tar.gz) The extracted archive contains the archived Docker image (bryne_docker_image.tar.gz), the Bryne code git archive, and a Readme with basic Docker instructions With the Docker engine active, you can load the Docker image with docker load -i bryne_docker_image.tar.gz The image is now available with the tag displayed by the load command. You can also check the image tag in the Readme .txt file. To use the following commands, simply replace $BRYNE_DOCKER_IMAGE with this image tag. Optional: If you store the tag in an environment variable such as export BRYNE_DOCKER_ IMAGE=registry.git.rwth-aachen.de/mbd/bryne/bryne:1.1.0 you can simply copy-paste the following commands. Replace the version number after the ":" with the version number of the Zenodo record. Extract the source archive folder (e.g. bryne_repo_VERSION) and navigate into it. You can open a JupyterLab server to navigate the repo and run the examples and tests with the command docker run -w /root/shared --init -p 8888:8888 -v "$(pwd)":/root/shared $BRYNE_DOCKER_IMAGE (replace $BRYNE_DOCKER_IMAGE with the image tag from the readme file)