This repository contains the code for the paper "CUQIpy – Part II: computational uncertainty quantification for PDE-based inverse problems in Python".
Install the package using pip (assuming python is installed):
pip install cuqipy
Some examples require additional packages like the plugins for FEniCS. These can be installed following the instructions on:
The examples (scripts and notebooks) are organized by folders, one folder for each of the 4 case studies (Poisson, Heat 1D, EIT, and PAT). To run the examples that are written as Jupyter notebooks, you need to install Jupyter. One can also view the notebooks on GitHub by clicking on the notebook files in the folders.
The following case studies are included in this repository:
- Section 1: Introduction 2D Poisson example in the folder
Poisson - Section 2: Framework for PDE-based Bayesian inverse problems in CUQIpy 1D Heat example in the folder
heat_1D, seeheat_1D/README.mdfor instructions on how to run the scripts. - Section 4: CUQIpy-FEniCS example: Electrical Impedance Tomography (EIT) EIT example in the folder
EIT, seeEIT/README.mdfor instructions on how to run the scripts - Section 5: Photo-acoustic tomography through user-defined PDE models PAT example in the folder
PAT, seePAT/README.mdfor instructions on how to run the scripts