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numpy /
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.gitignore | Mon Oct 11 23:19:28 -0700 2010 | |
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COMPATIBILITY | Sat Apr 21 21:29:42 -0700 2007 | |
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DEV_README.txt | Fri Oct 08 07:59:50 -0700 2010 | |
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INSTALL.txt | Sat Apr 04 03:28:48 -0700 2009 | |
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LICENSE.txt | Thu Jan 08 18:14:35 -0800 2009 | |
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MANIFEST.in | Wed Aug 04 05:01:29 -0700 2010 | |
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README.txt | Thu Sep 16 07:01:34 -0700 2010 | |
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TEST_COMMIT | Thu Jan 14 18:02:30 -0800 2010 | |
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THANKS.txt | Mon Jan 05 13:51:18 -0800 2009 | |
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benchmarks/ | Fri Feb 08 02:54:01 -0800 2008 | |
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branding/ | Tue Mar 10 23:41:48 -0700 2009 | |
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doc/ | Sat Oct 09 23:34:25 -0700 2010 | |
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numpy/ | Tue Oct 12 08:46:28 -0700 2010 | |
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pavement.py | Sat Sep 04 03:10:42 -0700 2010 | |
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release.sh | Mon Nov 30 09:35:24 -0800 2009 | |
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setup.py | Sat Sep 04 02:51:57 -0700 2010 | |
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setupegg.py | Wed Aug 25 05:40:23 -0700 2010 | |
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setupscons.py | Sat May 16 02:46:10 -0700 2009 | |
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setupsconsegg.py | Wed Aug 20 16:02:44 -0700 2008 | |
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site.cfg.example | Sun May 18 06:24:43 -0700 2008 | |
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tools/ | Thu Sep 16 07:01:34 -0700 2010 |
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()'
The most current development version is always available from our
git repository:
http://github.com/numpy/numpy
