Technical Details
Dependencies
PyPEEC is entirely programmed in Python 3 and has the following dependencies:
SciLogger, SciSave, and jsonschema (logging and serialization)
NumPy, SciPy, and Joblib (basic numerical computing libraries)
Shapely and Rasterio (only used for the mesher, 2D shape manipulation)
Pillow (only used for the mesher, 2D image manipulation)
VTK and PyVista (only used for for the mesher, 3D shape manipulation)
Additionally, the following libraries are used for the plotter and viewer:
Matplotlib and PyQt5 (2D plots)
VTK, PyVista, PyVistaQt, and PyQt5 (3D plots)
The following optional packages can be used for speeding up the solver:
PyAMG (pure Python solver)
UMFPACK (available through SciKits)
MKL/PARDISO (available through Pydiso)
FFTW (available through pyFFTW)
CuPy (using GPUs through CUDA)
If you deploy PyPEEC on computing nodes, the GUI libraries (Matplotlib, PyVistaQt, PyQt5) are not required. Inside Jupyter notebooks, IPyWidgets and Trame are used for the rendering.
Supported Platforms
The main target platform of PyPEEC is Linux on x86/x64:
Linux / RedHat 7.9 on x86/x64
Linux / RedHat 8.7 on x86/x64
Linux / Debian 12.4 on x86/x64
Linux / Ubuntu 20.04 on x86/x64
Linux / Ubuntu 22.04 on x86/x64
Linux / Ubuntu 24.04 on x86/x64
The following platforms and systems have been partially tested:
Apple macOS Monterey 12 on x86/x64
Apple macOS Ventura 13 on ARM64
Apple macOS Sonoma 14 on ARM64
MS Windows / Pro 10 on x86/x64
MS Windows / Pro 11 on x86/x64
The following GPUs have been tested (CUDA / CuPy compatible):
NVIDIA RTX 2070
NVIDIA RTX 3090
NVIDIA T4 Tensor
NVIDIA Tesla K80
The following platforms are passing the automated tests:
Linux / Ubuntu 22.04 on x86/x64 / Conda / PyPi
Microsoft / Windows Server 2022 on x86/x64 / Conda / PyPi
Apple / macOS Sonoma 14 on ARM64 / Conda
The following Python version are passing the automated tests:
CPython 3.10
CPython 3.11
CPython 3.12
Logger and Data Serialization
For the logger, PyPEEC is using SciLogger:
Custom logger configuration files can be set with the
SCILOGGER
environment variable.More information about the logging module: https://github.com/otvam/scilogger
For the serialization, PyPEEC is using SciSave:
The input/configuration files are either JSON or YAML files.
The output/data files are either JSON or Pickle files.
More information about the serialization module: https://github.com/otvam/scisave
Packaging and Environment
The following files are describing the package, documentation, and dependencies:
List of Python dependencies (pinned versions):
requirements.txt
Package definition with dependencies (minimum versions):
pyproject.toml
Conda file with the minimum requirements for PyPEEC:
conda_base.yaml
Conda file including the optional and development packages:
conda_dev.yaml
Conda feedstock recipe: https://github.com/conda-forge/pypeec-feedstock
The examples and the tutorial are located in the
examples
folder.The Sphinx documentation is located in the
docs
folder.
The following scripts are used to build the package, documentation, and releases:
scripts/run_build.sh
: build the Python package and build the HTML documentation.scripts/run_release.sh
: create a release (tag, release, package, and documentation).
Tests and Coverage
PyPEEC is using different tests to check for potential regressions:
The tests are located in the
tests
folder.The tests are using the
unittest
framework.The tests are covering all the main functionalities.
The tests are using the examples and the tutorial to check the code.
Only integration tests are currently implemented (no unit tests).
These files are used to run the tests (locally and/or continuous integration):
scripts/run_tests.sh
: run all the integration tests.scripts/run_coverage.sh
: run a code coverage analysis.
Contributing
PyPEEC is welcoming contributions (code, documentation, example, benchmark, test, tutorial, etc.)! For large changes, please first discuss the change you wish to make in the issue tracker.
Bug report
Please include a clear and concise description of what the bug is. Ideally, provide a minimal working example for the bug.
Additionally, please report the following parameters:
The version of the PyPEEC you are using.
The platform/hardware you are using.
The version of Python and of the relevant dependencies.
For PyVista related bugs, please include the
pyvista.Report
output.For NumPy related bugs, please include the
numpy.show_config
output.For SciPy related bugs, please include the
scipy.show_config
output.