bsplyne 1.0.4

N-dimensional B-spline library for numerical mechanics and geometry

bsplyne

bsplyne is a Python library for working with N-dimensional B-splines, with a focus on numerical mechanics and geometry. It implements the Cox–de Boor algorithm for basis evaluation, order elevation, knot insertion, and provides tools for handling multi-patch B-spline structures. Visualization and export utilities (e.g. Paraview) are also included.

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Installation

From PyPI (recommended method)

Install the core library:

pip install bsplyne

Install the library with recommended visualization features (additionally install pyvista):

pip install bsplyne[viz]

Note: choose either the core (bsplyne) or the visualization (bsplyne[viz]) installation.

From source (development mode)

Clone the repository and install:

git clone https://github.com/Dorian210/bsplyne
cd bsplyne
pip install -e .       # core
pip install -e .[viz]  # with visualization

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Dependencies

Core dependencies are handled automatically by pip:

• numpy
• numba
• scipy
• matplotlib
• meshio
• tqdm

Optional visualization:

• pyvista (for 3D visualization)

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Main Modules

• BSplineBasis
  Evaluation of B-spline basis functions using the Cox–de Boor recursion formula.

• BSpline
  Construction and manipulation of N-dimensional B-splines, including order elevation and knot insertion.

• MultiPatchBSplineConnectivity
  Management of connectivity between multiple B-spline patches.

• CouplesBSplineBorder
  Utilities for coupling B-spline borders (experimental / less documented).

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Tutorials

A step-by-step introduction to bsplyne is provided in:

examples/tutorial/

These scripts are designed as a progressive entry point to the library and cover:

1. B-spline basis functions
2. Curve construction
3. Surface generation
4. Least-squares fitting
5. Multi-patch geometries
6. Export to Paraview

In addition, a comprehensive PDF guide (tp_bsplyne.pdf) is included in the tutorials directory, providing a hands-on introduction to the library for new users.
It explains the workflow, the main modules, and practical usage examples.

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Examples

Additional standalone examples are available in the examples/ directory, including:

• Curves and surfaces
• Order elevation and knot insertion
• Visualization with Matplotlib
• Export to Paraview

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Documentation

The full API documentation is available online:

https://dorian210.github.io/bsplyne/

The documentation is generated from the source code docstrings and reflects the latest published version.

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Contributions

This project is primarily developed for research purposes. While I am not actively reviewing external contributions, bug reports and suggestions are welcome via the issue tracker.

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License

This project is licensed under the CeCILL License.
See LICENSE.txt for details.