| Name | numpy-minmax JSON |
| Version |
0.3.1
JSON |
| download |
| home_page | None |
| Summary | A fast python library for finding both min and max value in a NumPy array |
| upload_time | 2024-08-15 08:11:54 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | None |
| license | MIT License Copyright (c) 2024 Nomono Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
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| VCS |
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| bugtrack_url |
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| requirements |
No requirements were recorded.
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No Travis.
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| coveralls test coverage |
No coveralls.
|
# 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/AVX512 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
[](https://pypi.org/project/numpy-minmax/)
```
$ pip install numpy-minmax
```
# Usage
```py
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
## [0.3.1] - 2024-08-15
### Changes
* Optimize (with AVX) the processing of contiguous int16 arrays. ~2.3x speedup compared to 0.3.0
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`
# Running benchmarks
* Install diplib `pip install diplib`
* `python scripts/perf_benchmark.py`
# Acknowledgements
This library is maintained/backed by [Nomono](https://nomono.co/), a Norwegian audio AI startup.
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"description": "# numpy-minmax: a fast function for finding the minimum and maximum value in a NumPy array\n\nNumPy 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.\n\n* Written in C and takes advantage of AVX/AVX512 for speed\n* Roughly **2.3x speedup** compared to the numpy amin+amax equivalent (tested on Intel CPU with numpy 1.24-1.26)\n* 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.\n\n# Installation\n\n[](https://pypi.org/project/numpy-minmax/)\n\n\n\n```\n$ pip install numpy-minmax\n```\n\n# Usage\n\n```py\nimport numpy_minmax\nimport numpy as np\n\narr = np.arange(1337, dtype=np.float32)\nmin_val, max_val = numpy_minmax.minmax(arr) # 0.0, 1336.0\n```\n\n# Changelog\n\n## [0.3.1] - 2024-08-15\n\n### Changes\n\n* Optimize (with AVX) the processing of contiguous int16 arrays. ~2.3x speedup compared to 0.3.0\n\nFor the complete changelog, go to [CHANGELOG.md](CHANGELOG.md)\n\n# Development\n\n* Install dev/build/test dependencies as denoted in pyproject.toml\n* `CC=clang pip install -e .`\n* `pytest`\n\n# Running benchmarks\n* Install diplib `pip install diplib`\n* `python scripts/perf_benchmark.py`\n\n# Acknowledgements\n\nThis library is maintained/backed by [Nomono](https://nomono.co/), a Norwegian audio AI startup.\n",
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