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Merge pull request #5264 from njwilson23/master

ignore zero-length edges for default epsilon
latest commit 48048e7442
@ev-br ev-br authored
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benchmarks MAINT: inform asv where io_matlab.StructArr tests start making sense
doc Merge pull request #5140 from sargas/codata-2014
scipy BUG: ignore zero-length edges for default epsilon
tools MAINT: tools/refguide_check: recognize math label and eq
.coveragerc MAINT: add .coveragerc file to limit content of .coverage file to scipy.
.gitattributes MAINT: drop Cython from .gitattributes (no longer in repo)
.gitignore ENH: Initial version of lsq_linear
.gitmodules DOC: link to numpydoc via a git submodule
.travis.yml CI: move refguide check to top of travis matrix
BENTO_BUILD.txt BLD: some updates to Bento config files and docs. Closes gh-3978.
HACKING.rst.txt DOC: remove outdated info from HACKING.txt
INSTALL.rst.txt DOC: fix Numpy version requirement in INSTALL.rst.txt
LICENSE.txt Fix PEP8 W391 issues (blank line at end of file). MAINT: don't bundle everything in benchmarks/* to installation
README.rst Fix PEP8 W391 issues (blank line at end of file).
THANKS.txt BUG: stats: improve the numerical stability of hypergeom.logsf MAINT: change download URL from SourceForge to Github Releases.
bscript BLD: some updates to Bento config files and docs. Closes gh-3978. MAINT: change download URL from SourceForge to Github Releases. REL: update release scripts before 0.16.x branching. MAINT: fix call to refguide_check DOC: update PyPi trove classifiers. Beta -> Stable. Add license. Revert "MAINT: remove setup*egg*.py -- always use setuptools, if pres…
site.cfg.example DOC: update site.cfg.example. Mostly taken over from Numpy
tox.ini BLD: ignore pep8 E302 (expected 2 blank lines, found 1)



What is 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. It is also the name of a very popular conference on scientific programming with Python.

The SciPy library depends on NumPy, which provides convenient and fast N-dimensional array manipulation. The SciPy library 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!


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