SciPy

SciPy(发音为“Sigh Pie”)是一个基于Python的开源数据、科学和工程软件生态系统。 (SciPy (pronounced “Sigh Pie”) is a Python-based ecosystem of open-source software for mathematics, science, and engineering.)

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SciPy(发音为“Sigh Pie”)是一个基于Python的开源数据、科学和工程软件生态系统。 特别而言,包括如下一些核心包:

  • NumPy —— 基本N维阵列包。
  • SciPy库 —— 科学计算基础库。
  • Matplotlib —— 综合2D绘图。
  • IPython的 —— 增强型互动控制台;
  • Sympy —— 符号数学。
  • Pandas —— 数据结构与分析。
Python的科学计算工具
SciPy是指几个相关但不同的实体:
  • SciPy Stack是Python中科学计算的开源软件的集合,特别是一组指定的核心包。
  • 使用和开发这个栈的人的社区。
  • 几个致力于Python中科学计算的会议--SciPy,EuroSciPy和SciPy.in。
  • SciPy库是SciPy栈的一个组件,它提供了许多数值例程。

SciPy栈核心软件包

  • Python,通用编程语言。它被解释和动态输入,非常适合于交互式工作和快速原型设计,同时强大到足以编写大型应用程序。
  • NumPy,数值计算的基础包。它定义了数组和矩阵类型以及基本操作。
  • SciPy library,数字算法和领域专用工具箱的集合,包括信号处理,优化,统计等等。
  • Matplotlib是一种成熟和流行的绘图软件,提供出版品质的2D绘图以及初步的3D绘图
  • pandas,提供高性能,易于使用的数据结构。
  • SymPy,用于符号数学和计算机代数。
  • IPython 是一个丰富的交互式界面,可让您快速处理数据和测试想法。 IPython笔记本在您的网络浏览器中运行,可以让您以轻松可重复的形式记录您的计算。
  • nose,一个测试Python代码的框架。
其他包
  • 在这个栈上建立了许多更多的包 - 太多了,在这里难以一一列出。这是几个主要的简要概述:
  • Chaco 是另一个Python绘图工具包,从根本上设计成非常适合嵌入式,互动式绘图。它是建立在Traits上的,都是Enthought Tool Suite的一部分。
  • Mayavi 是一个功能强大且用户友好的3D可视化框架,建立在获奖的Visualization Toolkit VTK 之上。
  • Cython 扩展了Python语法,以便您可以方便地构建C扩展,以加快关键代码或与C /C ++库集成。
  • Scikits 是更多特定功能的额外包。scikit-imagescikit-learn是最突出的两个。
  • h5pyPyTables 都可以访问以HDF5格式存储的数据。

有关更多信息,请参阅“专题软件”页面。

Overview

Name With Ownerscipy/scipy
Primary LanguagePython
Program languagePython (Language Count: 12)
Platform
License:BSD 3-Clause "New" or "Revised" License
Release Count163
Last Release Namev1.13.0 (Posted on 2024-04-02 12:36:07)
First Release Namev0.1.0 (Posted on )
Created At2011-03-09 18:52:03
Pushed At2024-04-21 18:18:38
Last Commit At
Stargazers Count12.4k
Watchers Count348
Fork Count5k
Commits Count32.2k
Has Issues Enabled
Issues Count9895
Issue Open Count1508
Pull Requests Count8615
Pull Requests Open Count294
Pull Requests Close Count1725
Has Wiki Enabled
Is Archived
Is Fork
Is Locked
Is Mirror
Is Private

SciPy

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SciPy (pronounced "Sigh Pie") is open-source software for mathematics,
science, and engineering. It includes modules for statistics, optimization,
integration, linear algebra, Fourier transforms, signal and image processing,
ODE solvers, and more.

SciPy depends on NumPy, which provides convenient and fast
N-dimensional array manipulation. SciPy is built to work with
NumPy arrays, and provides many user-friendly and efficient numerical routines,
such as routines for numerical integration and optimization. Together, they
run on all popular operating systems, are quick to install, and are free of
charge. NumPy and SciPy are easy to use, but powerful enough to be depended
upon by some of the world's leading scientists and engineers. If you need to
manipulate numbers on a computer and display or publish the results, give
SciPy a try!

For the installation instructions, see INSTALL.rst.txt_.

We appreciate and welcome contributions. If you would like to take part in
SciPy development, take a look at the file CONTRIBUTING.rst_.

.. _CONTRIBUTING.rst: https://github.com/scipy/scipy/blob/master/CONTRIBUTING.rst
.. _INSTALL.rst.txt: https://github.com/scipy/scipy/blob/master/INSTALL.rst.txt

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