https://github.com/nomonosound/numpy-rms

Calculate RMS swiftly (SIMD-accelerated)
https://github.com/nomonosound/numpy-rms

arm-neon c float32 numpy numpy-library python simd x86-64

Last synced: 14 days ago
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Calculate RMS swiftly (SIMD-accelerated)

• Host: GitHub
• URL: https://github.com/nomonosound/numpy-rms
• Owner: nomonosound
• License: mit
• Created: 2024-04-05T12:46:47.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-10-09T06:46:28.000Z (3 months ago)
• Last Synced: 2024-11-16T01:39:32.343Z (about 1 month ago)
• Topics: arm-neon, c, float32, numpy, numpy-library, python, simd, x86-64
• Language: Python
• Homepage:
• Size: 52.7 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 4
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • License: LICENSE

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README

        
# 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

[![PyPI version](https://img.shields.io/pypi/v/numpy-rms.svg?style=flat)](https://pypi.org/project/numpy-rms/)

![python 3.8, 3.9, 3.10, 3.11, 3.12](https://img.shields.io/badge/Python-3.8%20|%203.9%20|%203.10%20|%203.11|%203.12-blue)

![os: Linux, macOS, Windows](https://img.shields.io/badge/OS-Linux%20%28arm%20%26%20x86%29%20|%20macOS%20%28arm%20%26%20x86%29%20|%20Windows%20%28x86%29-blue)

```

$ pip install numpy-rms

```

# Usage

```py

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](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](https://nomono.co/), a Norwegian audio AI startup.