A fast python library for calculating the RMS of a NumPy array

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Project description

numpy-rms: a fast function for calculating a series of Root Mean Square (RMS) values

Written in C and takes advantage of AVX2 for speed
The fast implementation is tailored for contiguous 1-dimensional float32 arrays

Installation

python 3.8, 3.9, 3.10, 3.11, 3.12 os: Linux, Windows CPU: x86_84

$ 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

See 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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This version

0.1.0

Apr 11, 2024

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