We provide a collection of example notebooks to get a better idea of how to use pyABC, and illustrate core features.
The notebooks can be run locally with an installation of jupyter (pip install jupyter), or online on Google Colab or nbviewer, following the links at the top of each notebook. To run the notebooks online, at least an installation of pyABC is required, which can be performed by
# install if not done yet
!pip install pyabc --quietPotentially, further dependencies may be required. Unfortunately, at the moment (2022-06), Google Colab is using Python 3.7, while pyABC and many other packages have proceeded to require Python >= 3.8. Thus, not everything may work properly.
examples/parameter_inference.ipynb examples/model_selection.ipynb
examples/early_stopping.ipynb examples/resuming.ipynb examples/custom_priors.ipynb examples/adaptive_distances.ipynb examples/informative.ipynb examples/aggregated_distances.ipynb examples/wasserstein.ipynb examples/data_plots.ipynb examples/noise.ipynb examples/optimal_threshold.ipynb examples/discrete_parameters.ipynb examples/look_ahead.ipynb
examples/using_R.ipynb examples/using_julia.ipynb examples/external_simulators.ipynb examples/petab_yaml2sbml.ipynb examples/using_copasi.ipynb
examples/conversion_reaction.ipynb examples/chemical_reaction.ipynb examples/multiscale_agent_based.ipynb examples/sde_ion_channels.ipynb examples/petab_application.ipynb
Warning
Upgrade to the latest pyABC version before running the examples. If you installed pyABC some weeks (or days) a ago, some new features might have been added in the meantime. Refer to the upgrading section on how to upgrade pyABC.