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Refactoring repo (temporary)
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doc Merge commit '8cbed8ce5253a0aa4341e6edbf8be123a06bb123' (Nov 18) into…
libndarray Updates to support 64-bit builds. Builds but getting crash in test_mu…
numpy Updates to support 64-bit builds. Builds but getting crash in test_mu…
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COMPATIBILITY Add loadtxt and savetxt adapted from matplotlib.
DEV_README.txt DOC: Change mention of SVN to Git.
INSTALL.txt Mention nose for requirements.
LICENSE.txt Updated license file
MANIFEST.in ENH: include /*.txt etc. in source dist only, rather than installing it
README.txt DOC: recommend to turn on deprecation warnings for Python >= 2.7.
TEST_COMMIT test commit
THANKS.txt Credit more developers.
iron_egg.py Fixed paths to remove 'Release' directory. We are just putting files …
iron_install.py fixed DLLs included in egg
iron_setup.py Fixed consistency of iron* iron_* scripts.
pavement.py REL: Apply changes to release notes and paver script in 1.5.x branch …
release.sh REL: generate both 2.5 and 2.6 win and mac os x installers in release…
setup.py add git_version() to setup.py
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README.txt

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://scipy.org/NumPy

After installation, tests can be run with:

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

When installing a new version of numpy for the first time or before upgrading
to a newer version, it is recommended to turn on deprecation warnings when
running the tests:

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

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

http://github.com/numpy/numpy


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