A fast python library for finding both min and max value in a NumPy array

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License: MIT License (MIT License Copyright (c) 2024 Nomono Permission is hereby granted, free of charge, to any person ...)

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Project description

numpy-minmax: a fast function for finding the minimum and maximum value in a NumPy array

NumPy lacked an optimized minmax function, so we wrote our own. At Nomono, we use it for audio processing, but it can be applied any kind of float32 ndarray.

  • Written in C and takes advantage of AVX for speed
  • Roughly 2.3x speedup compared to the numpy amin+amax equivalent (tested on Intel CPU with numpy 1.24-1.26)
  • The fast implementation is tailored for float32 arrays that are C-contiguous, F-contiguous or 1D strided. Strided arrays with ndim >= 2 get processed with numpy.amin and numpy.amax, so no perf gain there.

Installation

PyPI version python 3.8, 3.9, 3.10, 3.11, 3.12 os: Linux, Windows CPU: x86_84

$ pip install numpy-minmax

Usage

import numpy_minmax
import numpy as np

arr = np.arange(1337, dtype=np.float32)
min_val, max_val = numpy_minmax.minmax(arr)  # 0.0, 1336.0

Changelog

See CHANGELOG.md

Development

  • Install dev/build/test dependencies as denoted in pyproject.toml
  • CC=clang pip install -e .
  • pytest

Running benchmarks

  • Install diplib pip install diplib
  • python scripts/perf_benchmark.py

Acknowledgements

This library is maintained/backed by Nomono, a Norwegian audio AI startup.

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License: MIT License (MIT License Copyright (c) 2024 Nomono Permission is hereby granted, free of charge, to any person ...)

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