A fast python library for calculating the RMS of a NumPy array
Project description
numpy-rms: a fast function for calculating a series of Root Mean Square (RMS) values
- Written in C and takes advantage of AVX (on x86-64) or NEON (on ARM) for speed
- The fast implementation is tailored for C-contiguous 1-dimensional and 2-dimensional float32 arrays
Installation
$ pip install numpy-rms
Usage
import numpy_rms
import numpy as np
arr = np.arange(40, dtype=np.float32)
rms_series = numpy_rms.rms(arr, window_size=10)
print(rms_series.shape) # (4,)
Changelog
[0.4.2] - 2024-07-13
Changed
- Optimize the processing of multichannel arrays
For the complete changelog, go to CHANGELOG.md
Development
- Install dev/build/test dependencies as denoted in pyproject.toml
CC=clang pip install -e .
pytest
Acknowledgements
This library is maintained/backed by Nomono, a Norwegian audio AI startup.
Project details
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