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Source: numpy-rms
Maintainer: Home Assistant Team <team+homeassistant@tracker.debian.org>
Uploaders:
Edward Betts <edward@4angle.com>,
Section: python
Build-Depends:
debhelper-compat (= 13),
dh-sequence-python3,
pybuild-plugin-pyproject,
python3-all-dev,
python3-cffi,
python3-numpy,
python3-pytest <!nocheck>,
python3-pytest-benchmark <!nocheck>,
python3-setuptools,
Standards-Version: 4.7.3
Homepage: https://github.com/nomonosound/numpy-rms
Vcs-Browser: https://salsa.debian.org/homeassistant-team/deps/numpy-rms
Vcs-Git: https://salsa.debian.org/homeassistant-team/deps/numpy-rms.git
Testsuite: autopkgtest-pkg-pybuild
Package: python3-numpy-rms
Architecture: any
Depends:
${misc:Depends},
${python3:Depends},
${shlibs:Depends},
Description: fast root mean square calculation for NumPy arrays
This library provides a fast implementation of root mean square (RMS)
calculations for NumPy arrays. It computes RMS values over fixed-size windows
and returns the resulting series.
.
The function operates on one-dimensional or two-dimensional float32 arrays
stored in contiguous memory. Given an input array and a window size, it
calculates the RMS value for each window, producing a sequence of RMS values.
This is useful for summarising signal magnitude over time or across grouped
samples.
.
The implementation is written in C and includes architecture-specific
optimisations for x86-64 (AVX) and ARM (NEON) systems, allowing efficient
processing of large arrays where repeated RMS calculations would otherwise be
costly.
.
The module focuses on a single task: efficient RMS computation for NumPy array
data. It does not attempt to provide a full signal-processing framework.
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