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# 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
[](https://pypi.org/project/numpy-rms/)
```
$ 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
## [0.6.0] - 2025-06-29
### Added
* Add support for Python 3.13
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.
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