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.