Pacote: python3-numpy-rms (0.6.0-1) [debports]

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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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