Known Issues

PyPEEC Issues

Warning

The geometry is meshed with a regular voxel structure (uniform grid). This implies that large geometries with small features cannot be meshed efficiently.

Warning

For problems with magnetic domains, the preconditioner is not optimal. This might lead to a slow convergence of the iterative matrix solver. For such cases, using a segregated solver might be useful.

Warning

For large problems, the code might allocate huge amounts of memory. This might crash the program and/or your operating system.

Warning

During the voxelization process, the same voxel can be assigned to several domains. The problem is solved with used-provided conflict resolution rules between the domains.

Library Issues

Warning

The plotting code is probably sensitive to the environment (platform and the version of the libraries). Therefore, these dependencies are minimized and insulated from the rest of the code. The plotting code (viewer and plotter) is separated from the simulation code (mesher and solver).

Warning

Jupyter is not included in the package dependencies. Inside Jupyter notebooks, IPyWidgets and Trame are used for the rendering. Jupyter support is optional, PyPEEC is fully functional without Jupyter.

Warning

The GPU libraries (CuPy and CUDA) are not included in the package dependencies. The GPU support is extremely hardware/platform/version dependent. GPU support is optional, PyPEEC is fully functional without GPU support.

Warning

FFTW, UMFPACK, PyAMG, and MKL/PARDISO are not included in the package dependencies. These libraries can be tricky to install, especially on MS Windows. Make sure that these libraries are compiled with multithreading support. FFTW, UMFPACK, PyAMG, and MKL/PARDISO are optional, PyPEEC is fully functional without them.

General Issues

Warning

Python Pickle files can be used to store the mesher and solver results. Pickling data is not secure. Only load Pickle files that you trust. JSON or GZIP/JSON files can be used to solve this problem.

Warning

The dependencies are under various licences. Make sure to respect these licenses if you package and/or distribute these libraries. Qt is under a copyleft license (LGPL and GPL). FFTW is also under a copyleft license (GPL). MKL/PARDISO and CUDA are proprietary software (these libraries are optional).