Documentation
The complete API reference of hIPPYlib is available at readthedocs.
Algorithms implemented in hIPPYlib are described in
Umberto Villa, Noemi Petra, and Omar Ghattas. 2021. HIPPYlib: An Extensible Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference. ACM Trans. Math. Softw. 47, 2, Article 16 (March 2021), 34 pages. arXiv
Installation of stable releases
The latest hIPPYlib release depends on FEniCS versions 2019.1.
FEniCS needs to be built with the following dependecies:
numpy,scipy,matplotlib,mpi4pyPETScandpetsc4py(version 3.7.0 or above)SLEPcandslepc4py(version 3.7.0 or above)- PETSc dependencies:
parmetis,scotch,suitesparse,superlu_dist,ml,hypre - (optional):
mshr,jupyter
For detailed installation instructions of the latest stable release see here.
Custom Docker Images and conda packages for FEniCS 2019.1.0
While hIPPYlib can be used with the Docker images and conda packages from the ufficial FEniCS packages,
a customized FEniCS docker image and customized conda packages is available.
hIPPYlib 2.3.0 Docker container
A Docker image with a working installation of hIPPYlib 2.3.0 and FEniCS 2017.2 is available here. Numerical results presented in the manuscript hIPPYlib: A Software Framework for Large-Scale Inverse Problems Governed by PDEs: Part I: Deterministic Inversion and Linearized Bayesian Inference were obtained using the software in this image.