skfem-native
skfem-native provides skfemntv, a native numerical assembly backend with a
scikit-fem-style Python API. It keeps finite-element formulations in readable
Python while accelerating reusable assembly, geometry, and sparse-scatter
kernels in native code.
Motivation
The project exists to improve the performance of Python assembly workflows represented by scikit-fem without replacing their Python programming model. Weak forms, nonlinear constitutive updates, contact formulations, and solver policy remain ordinary Python components; stable and reusable numerical kernels are moved to native code where doing so provides a practical benefit.
This boundary is becoming more important in the era of AI-assisted coding. Application-specific nonlinear formulations can now be developed, reviewed, and revised rapidly when they remain small, explicit Python components. Libraries such as scikit-fem therefore become more valuable, not less: they provide a transparent mathematical vocabulary while avoiding the cost of embedding every new formulation in a monolithic compiled solver.
skfem-native aims to combine that flexibility with faster assembly. It is a
selectable backend for Python finite-element applications, not a separate owner
of their material models or physical formulations.
Installation
python -m pip install skfem-native
The distribution is named skfem-native; import it as skfemntv.
Quick start
import skfemntv
from skfemntv.helpers import dot, grad
mesh = skfemntv.MeshTet()
basis = skfemntv.Basis(mesh, skfemntv.ElementTetP1())
@skfemntv.BilinearForm
def diffusion(u, v, w):
return dot(grad(u), grad(v))
matrix = skfemntv.asm(diffusion, basis)
Applications can select skfem.asm or skfemntv.asm at their backend
boundary while preserving the weak-form call site. skfemntv is not yet a
complete replacement for every scikit-fem feature, so backend selection should
remain explicit.
For the supported mesh, element, basis, and assembly subset, the compatibility target is stronger: changing
import skfem
to
import skfemntv as skfem
should preserve public DOF ordering and numerical results. Higher-order DOFs are numbered by topological entity, following scikit-fem: vertices first, shared edges or facets next, and element interiors last. This makes assembled vectors and matrices directly interchangeable without a coordinate permutation.
Solver conveniences such as solve, enforce, and penalize are outside the
native assembly backend. Applications may continue to use scikit-fem or SciPy
for these operations.
Capabilities
- functional, linear, bilinear, and cross-bilinear assembly
- meshes, elements, bases, tabulation, and quadrature
- caller-supplied tensor coefficient assembly
- threaded native kernels and sparse scatter
- cut-cell and implicit-interface quadrature
- interface supermeshes and contact-facet search
Assembly performance
The following reference run compares warm-cache Poisson P1 matrix and right-hand-side assembly using identical meshes and spaces. Results depend on hardware, thread affinity, and package versions; they are an example rather than a universal performance guarantee.
See the benchmark methodology and recorded environment and values for details.
See DEVELOPMENT.md for the motivation, architecture boundary, and development principles.
Documentation
Build the Sphinx documentation locally:
python -m pip install -e '.[docs]'
sphinx-build -M html docs docs/_build
Open docs/_build/html/index.html after the build completes.
Development
python -m pip install -e '.[test]'
pytest -q
1 maintainer
Metadata
1 maintainer
Release files for skfem-native 0.2.1
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Source distribution (sdist)
| File | Size | Uploaded | |
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| skfem_native-0.2.1.tar.gz | 2.4 MB | Details |
Built distributions (wheels)
Total release size: 8.6 MB
Release files / skfem_native-0.2.1.tar.gz
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Transparency logRelease files / skfem_native-0.2.1-cp310-cp310-macosx_10_9_x86_64.whl
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