Bayesian workflow ================= Welcome to the Bayesian workflow course. Here, you can browse and search the course notebooks. This course is part of the ORIGINS Data Science Laboratory's Block courses. Please see the `main course page `_ for more information. Installation ------------ To run the course notebooks, you have a few different options. I recommend to follow the standard install, and use docker or binder if there are problems. .. note:: The notebooks have been tested with Python 3.9 and updates may need to be made to for Python > 3.9 to work. * **Plan A - Standard install:** Fork/clone/download material from this `GitHub repository `_, everything you need is in ``src/notebooks`` * I recommend using a `virtual environment `_ if possible * Install the basics if necessary: ``pip install numpy scipy matplotlib`` * Install: ``pip install cython==0.29.24 cmdstanpy==0.9.76 arviz==0.11.2 ultranest==3.3.0`` * Run ``install_cmdstan`` (as described in the `cmdstanpy docs `_) * If using a virtual environment, set up an ipython kernel with this environment (as described `here `_) * Open a notebook using jupyter, select correct kernel and get running * **Plan B - Docker:** Fork/clone/download material from this `GitHub repository `_, everything you need is in ``src/notebooks`` * Install `docker `_ on your computer * Get a ready made docker enironment: ``docker pull cescalara/bayesian_workflow`` * Run ``docker run -p 8888:8888 -v "${PWD}":/home/jovyan/work cescalara/bayesian_workflow jupyter-notebook --allow-root`` * Open the given url ``http://127.0.0.1:8888/lab?token=....`` in your browser * The current directory will be mounted to the docker and the jupyter server has the environment needed to run the notebooks * **Plan C - Binder:** Click `here `_ to launch a working environment via binder, all notebooks are in ``work/`` * The binder may take a while to load, this is normal * Using binder you will automatically time out of sessions if you are inactive for more than 10 minutes, so save your work frequently * The changes that you make are *not persistent* - if you close and repoen a tab your changes will be lost * To work continuously, download and upload your changes between active sessions Solutions --------- Complete solutions to the notebooks can be made available upon request. Please contact f.capel@tum.de. Acknowledgements ---------------- I would like to highlight the `many resources `_ of Michael Betancourt and the `KIPAC Statistical Methods course `_ as providing inspiration for the course structure and content. .. toctree:: :maxdepth: 1 :caption: Contents: notebooks/introduction.ipynb notebooks/model_building.ipynb notebooks/model_checking.ipynb notebooks/model_development.ipynb notebooks/model_comparison_part1.ipynb notebooks/example-sine-modelcomparison.ipynb notebooks/experiment_design.ipynb notebooks/homework_project.ipynb