Known Issues
PyPEEC Issues
Note
The geometry is meshed with a regular voxel structure (uniform grid). This implies that large geometries with small features cannot be meshed efficiently.
Note
If should be noted than the inductance is only fully defined for closed loops. For non-closed loops, only the concept of partial inductance is well defined.
Note
The magnetic near-field computation is done with lumped variables. Therefore, the computation is only accurate far away from the voxel structure.
Note
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 the segregated solver approach might be useful.
Note
It should be noted that surface charges are not considered. Only volume charges are used, which is an approximation.
Note
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
Important
The plotting code is probably sensitive to the environment (platform and 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).
Important
Jupyter is not included in the default package dependencies. Inside Jupyter notebooks, IPyWidgets Trame, and ipympl are used for the rendering. Jupyter support is optional, PyPEEC is fully functional without Jupyter.
Important
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.
Important
FFTW, PyAMG, MKL/FFT, and MKL/PARDISO are not included in the default package dependencies. These libraries can be tricky to install, especially on MS Windows or Apple MacOS. The aforementioned libraries 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 Docker image is only intended for test purposes. This image is not screened for eventual vulnerabilities. Do not use the image for public-facing servers.
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). INTEL/MKL and NVIDIA/CUDA are proprietary software (these libraries are optional).