The notebook pymc3_tutorial.ipynb contains a short PyMC3 tutorial. There we simulate some data using a sine function with amplitude A and wave number k as an underlying model. Then we add some Gaussian noise on top to emulate a mock observation. Finally using PyMC3 we infer the underlying parameters using MCMC chains.
In order to run the whole notebook you need the pymc3 python package for the inference section, as well as getdist (or pygtc) for the contour plots.
pip install pymc3pip install getdistand/or
pip install pygtc
