Skip to content
Scipy library main repository
Branch: master
Clone or download
rgommers Merge pull request #10072 from WarrenWeckesser/fix-boxcox
BUG: stats: Fix boxcox_llf to avoid loss of precision.
Latest commit bc493fc Apr 19, 2019
Type Name Latest commit message Commit time
Failed to load latest commit information.
.circleci MAINT: Undo sphinx pin [skip travis] [skip azp] [skip appveyor] Mar 29, 2019
benchmarks fixed benchmark Apr 16, 2019
scipy Merge pull request #10072 from WarrenWeckesser/fix-boxcox Apr 19, 2019
.gitattributes MAINT: reduce the number of git conflicts in the release notes Feb 13, 2017
.gitignore Merge pull request #8431 from mikofski/cython_optimize Apr 9, 2019
.gitmodules MAINT: bundle Mathjax for built documentation May 4, 2017
.mailmap DOC: update 1.2.0 release notes [ci skip] Nov 9, 2018
.travis.yml CI: enable pip build isolation (PEP 517) for one build. Apr 13, 2019
CONTRIBUTING.rst DOC: Replace Scipy with SciPy in the rst doc files for consistency. Nov 17, 2018
HACKING.rst.txt DOC: add dev setup description for PRs to local repo (#9674) Jan 18, 2019
LICENSE.txt BLD: BUG: include pyproject.toml in sdist Apr 13, 2019
README.rst MAINT: add Azure badge Dec 14, 2018
THANKS.txt TST: test fixes for sparse.csgraph Mar 13, 2019
appveyor.yml MAINT: remove extraneous distutils copies Mar 12, 2019
azure-pipelines.yml TST: Azure summarizes test failures Apr 5, 2019
codecov.yml CI: upload coverage also on failure (#8408) Feb 11, 2018 CI: pin Sphinx version to 1.8.5 Mar 28, 2019
pyproject.toml BLD: bump numpy version for py37 in pyproject.toml to 1.14.5 Apr 13, 2019
pytest.ini BUG: Catch internal warnings for matrix Feb 21, 2019 FIX: Fixes Jan 18, 2019 Add project_urls to setup Apr 12, 2019
site.cfg.example DOC: Misc. typos Oct 23, 2018



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 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.

You can’t perform that action at this time.