GitHub - njsmith/numpy at deprecate-int-float-etc

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branding/icons		branding/icons
doc		doc
numpy		numpy
tools		tools
.gitattributes		.gitattributes
.gitignore		.gitignore
.gitmodules		.gitmodules
.mailmap		.mailmap
.travis.yml		.travis.yml
BENTO_BUILD.txt		BENTO_BUILD.txt
COMPATIBILITY		COMPATIBILITY
CONTRIBUTING.md		CONTRIBUTING.md
DEV_README.txt		DEV_README.txt
INSTALL.txt		INSTALL.txt
LICENSE.txt		LICENSE.txt
MANIFEST.in		MANIFEST.in
README.txt		README.txt
TEST_COMMIT		TEST_COMMIT
THANKS.txt		THANKS.txt
bento.info		bento.info
bscript		bscript
pavement.py		pavement.py
release.sh		release.sh
runtests.py		runtests.py
setup.py		setup.py
setupegg.py		setupegg.py
site.cfg.example		site.cfg.example
tox.ini 72A1		tox.ini

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NumPy is the fundamental package needed for scientific computing with Python.
This package contains:

    * a powerful N-dimensional array object
    * sophisticated (broadcasting) functions
    * tools for integrating C/C++ and Fortran code
    * useful linear algebra, Fourier transform, and random number capabilities.

It derives from the old Numeric code base and can be used as a replacement for Numeric. It also adds the features introduced by numarray and can be used to replace numarray.

More information can be found at the website:

http://www.numpy.org

After installation, tests can be run with:

python -c 'import numpy; numpy.test()'

The most current development version is always available from our
git repository:

http://github.com/numpy/numpy