numpy/numpy

GitHub: numpy/numpy

NumPy 是 Python 科学计算的基础库,提供高性能的多维数组对象及线性代数、傅里叶变换等数值计算能力。

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[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)]( https://numfocus.org) [![PyPI Downloads](https://img.shields.io/pypi/dm/numpy.svg?label=PyPI%20downloads)]( https://pypi.org/project/numpy/) [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/numpy.svg?label=Conda%20downloads)]( https://anaconda.org/conda-forge/numpy) [![Stack Overflow](https://img.shields.io/badge/stackoverflow-Ask%20questions-blue.svg)]( https://stackoverflow.com/questions/tagged/numpy) [![Nature Paper](https://img.shields.io/badge/DOI-10.1038%2Fs41586--020--2649--2-blue)]( https://doi.org/10.1038/s41586-020-2649-2) [![LFX Health Score](https://insights.linuxfoundation.org/api/badge/health-score?project=numpy)](https://insights.linuxfoundation.org/project/numpy) [![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/numpy/numpy/badge)](https://securityscorecards.dev/viewer/?uri=github.com/numpy/numpy) [![Typing](https://img.shields.io/pypi/types/numpy)](https://pypi.org/project/numpy/) NumPy 是使用 Python 进行科学计算的基础包。 - **网站:** https://numpy.org - **文档:** https://numpy.org/doc - **邮件列表:** https://mail.python.org/mailman/listinfo/numpy-discussion - **源代码:** https://github.com/numpy/numpy - **贡献:** https://numpy.org/devdocs/dev/index.html - **Bug 报告:** https://github.com/numpy/numpy/issues - **报告安全漏洞:** https://github.com/numpy/numpy/security/policy (通过 Tidelift) 它提供了: - 强大的 N 维数组对象 - 复杂的(广播)功能 - 用于集成 C/C++ 和 Fortran 代码的工具 - 实用的线性代数、傅里叶变换和随机数功能 测试: NumPy 需要 `pytest` 和 `hypothesis`。安装后可以使用以下命令运行测试: ``` python -c "import numpy, sys; sys.exit(numpy.test() is False)" ```
标签:Python, 代码示例, 多维数组, 数学库, 数据分析, 无后门, 科学计算, 线性代数, 逆向工具