https://github.com/s0/scipy-demo
https://github.com/s0/scipy-demo
Last synced: about 2 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/s0/scipy-demo
- Owner: s0
- License: other
- Created: 2018-10-15T19:49:07.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2018-10-16T01:26:30.000Z (over 7 years ago)
- Last Synced: 2025-02-16T06:37:11.395Z (over 1 year ago)
- Language: Python
- Size: 74.1 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- Contributing: CONTRIBUTING.rst
- License: LICENSE.txt
- Code of conduct: .github/CODE_OF_CONDUCT.md
Awesome Lists containing this project
README
SciPy
=====
.. image:: https://img.shields.io/travis/scipy/scipy/master.svg?label=Travis%20CI
:target: https://travis-ci.org/scipy/scipy/
.. image:: https://img.shields.io/appveyor/ci/scipy/scipy/master.svg?label=AppVeyor
:target: https://ci.appveyor.com/project/scipy/scipy
.. image:: https://img.shields.io/circleci/project/github/scipy/scipy/master.svg?label=CircleCI
:target: https://circleci.com/gh/scipy/scipy
.. image:: https://codecov.io/gh/scipy/scipy/branch/master/graph/badge.svg
:target: https://codecov.io/gh/scipy/scipy
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.
- **Website (including documentation):** https://www.scipy.org/
- **Mailing list:** https://scipy.org/scipylib/mailing-lists.html
- **Source:** https://github.com/scipy/scipy
- **Bug reports:** https://github.com/scipy/scipy/issues
- **Code of Conduct:** https://scipy.github.io/devdocs/dev/conduct/code_of_conduct.html
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 installation instructions, see INSTALL.rst.txt_.
Developer information
---------------------
If you would like to take part in SciPy development, take a look
at the file CONTRIBUTING.rst_.
License information
-------------------
See the file LICENSE.txt_ for information on the history of this
software, terms & conditions for usage, and a DISCLAIMER OF ALL
WARRANTIES.
.. _LICENSE.txt: https://github.com/scipy/scipy/blob/master/LICENSE.txt
.. _CONTRIBUTING.rst: https://github.com/scipy/scipy/blob/master/CONTRIBUTING.rst
.. _INSTALL.rst.txt: https://github.com/scipy/scipy/blob/master/INSTALL.rst.txt