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Merge pull request #6199 from aarchiba/longdouble_scanf

BUG 4381 Longdouble from string without precision loss
latest commit 5d6a9f0030
@charris charris authored
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benchmarks WHT: break long lines + pep8
branding/icons add .gitattributes and fix line endings
doc Merge pull request #6245 from seberg/index-iter-bug
numpy MAINT clean up test suite
tools MAINT,TST: Remove Bento from the travis ci testing.
.gitattributes TST: Add tests for Python2, Python3 *.npy compatibility.
.gitignore MAINT: update .gitignore vs benchmarks
.gitmodules Add Numpydoc as a git submodule
.mailmap MAINT: Change an address in .mailmap
.travis.yml MAINT,TST: Remove Bento from the travis ci testing.
BENTO_BUILD.txt STY: Giant whitespace cleanup.
COMPATIBILITY Add loadtxt and savetxt adapted from matplotlib. MAINT give pointers to coding style and dev environment
DEV_README.txt STY: Giant whitespace cleanup.
INSTALL.txt DOC: update INSTALL.txt with info on binary installers and 32-bit Win…
LICENSE.txt MAINT: update year of copyright note in LICENSE.txt BLD: Move numpy.build_utils -> numpy._build_utils, add to
README.txt STY: Giant whitespace cleanup.
TEST_COMMIT Test commit to trigger buildbot -- ignore.
THANKS.txt ENH: core: Start einsum function, add copyright notices to files DOC: Add Trove classifiers for supported Python versions
bscript BLD: remove cython c source from git MAINT: Init master branch for 1.11.0 development. MAINT: update release scripts for building OS X binaries. WHT: break long lines + pep8 DOC: Add Trove classifiers for supported Python versions 2to3: Apply `print` fixer.
site.cfg.example Fix typo in site.cfg.example
tox.ini TST: Add Python 3.4 to Tox environments


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:

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:
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