Metadata-Version: 2.4
Name: smudgy
Version: 0.2.2
Summary: Point Cloud smoothing and interpolation package with Numpy and Taichi backends.
Author: Mauro Bernardini
Author-email: mauro.bernardini1313@gmail.com
Maintainer: Mauro Bernardini
Maintainer-email: mauro.bernardini1313@gmail.com
Project-URL: Homepage, https://github.com/maurbe/smudgy
Project-URL: Repository, https://github.com/maurbe/smudgy
Project-URL: Documentation, https://smudgy.readthedocs.io/en/latest/start/quickstart.html
Requires-Python: <3.14,>=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: taichi
Requires-Dist: mpi4py
Requires-Dist: tqdm
Provides-Extra: test
Requires-Dist: pytest; extra == "test"
Dynamic: license-file

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Welcome to the `smudgy` GitHub page!  `smudgy` is a high-performance Python package for smoothing, interpolation, and grid deposition of point-cloud data -- lightning fast, scalable and memory-efficient.

Whether you’re working on a laptop or an HPC cluster, `smudgy` is built to make efficient use of your hardware. It leverages the [Taichi](https://www.taichi-lang.org/) programming language for automatic CPU and GPU parallelization, and can seamlessly scale to multiple nodes using MPI through [mpi4py](https://mpi4py.github.io/mpi4py/stable/html/index.html).

Please refer to the official [docs](https://smudgy.readthedocs.io/en/latest/) for installation guides and tutorials.
