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Library for acoustic signal processing (Rust implementation of to-be-fast code). https://code.ascee.nl/ascee/lasprs
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J.A. de Jong - Redu-Sone B.V., ASCEE V.O.F. 016db92eba Wrapper for midband frequency of standard filter
2024-09-30 21:35:57 +02:00
.gitea/workflows Added sensible name for overlap 2024-09-26 21:57:03 +02:00
examples_py Added sensible name for overlap 2024-09-26 21:57:03 +02:00
python/lasprs TimeWeighting __eq__ method added. Improved comments. Tested Python code. Now ready for implementing WindowType Python wrapper 2024-08-28 21:51:16 +02:00
src Wrapper for midband frequency of standard filter 2024-09-30 21:35:57 +02:00
tools Bugfixing on SLM. First tests. Code seems to work, but might still have subtle bugs (as timeweighting was wrong previous to this commit). 2024-08-19 23:02:13 +02:00
.gitignore Added test files. Debugged quite some things. SLM needs still tests on statistics. Bugfix in frequency weighting filters. Added a lot of wrappers for Python calls. 2024-08-26 21:57:11 +02:00
Cargo.toml Let SLM::run output a vec of pyarrays, instead of vec of vecs 2024-09-30 14:26:10 +02:00
noxfile.py Version bump with wrappers 2023-11-25 15:01:40 +01:00
pyproject.toml Bugfixes for building Python extension module 2024-07-18 13:41:27 +02:00
README.md TimeWeighting __eq__ method added. Improved comments. Tested Python code. Now ready for implementing WindowType Python wrapper 2024-08-28 21:51:16 +02:00

README.md

LASPrs: Library for Acoustic Signal Processing in Rust

Welcome to LASPrs: Library for Acoustic Signal Processing. LASPrs is a rust library that provides tools and measurement software that enables the acquisition and processing of (multi) sensor data in real time on a PC and output results.

Note to potential users

This crate is still under heavy development. API changes happen on the fly. Documentation is not finished. Use with caution but except things to be broken and buggy.

Documentation

Documentation is provided at doc.rs.

Python bindings and examples

The library has Python bindings (via pyo3, which can be installed via:

$ pip install lasprs

which pulls the library from Pypi.

Examples of how to use the library are provided in Jupyter Notebooks, which can be found in the repository, see lasprs/examples_py.

More examples will follow in the near future.