On Sun, Jan 27, 2013 at 2:54 PM, Christoph Gohlke <[email protected]> wrote: > On 1/27/2013 11:40 AM, [email protected] wrote: >> Hi, >> >> if I want to have a painless Python installation build against Intel MKL on >> Windows, one obvious choice is to just buy the EPD package. However, >> as I already do have a C++ licence of the MKL library I was wondering if I >> could just install the Python(x,y) -distribution and then take one of the >> NumPy-MKL binaries provided >> by Christoph Gohlke. Is it simple as that? Any downsides, will SciPy work as >> well? On the plus side, I would get Spyder2 without hassle and it looks nice >> to a former Matlab user. >> >> I apologize for such a simple question, I would have tried it myself but >> this is for my work where only IT support has the admin rights and I have >> mac at home. I want it to be as >> clearcut for them as possible so I get things up and running. I did try to >> search the internet and the list but did not find a conclusive answer. >> >> Many thanks in advance for any help. >> >> All the best, >> >> Olli >> > > Try WinPython <http://code.google.com/p/winpython/>. It repackages > numpy-MKL and other packages from > <http://www.lfd.uci.edu/~gohlke/pythonlibs/>, contains Spyder and all > dependencies, is available as 64 bit, and does not require admin rights > to install.
You can replace python xy installed packages but it's necessary to watch out for dependencies. If you replace numpy with the mkl version, then you also have to replace scipy with the mkl version, as far as I understand. I initially installed python xy on a new computer and updated many packages since, using standard python not the python xy updates. The only problem I have is that I have some incompatibilities between QT, pyQT, pyside, spyder and the ipython qt console, the later doesn't work in my current setup. Josef > > Christoph > _______________________________________________ > NumPy-Discussion mailing list > [email protected] > http://mail.scipy.org/mailman/listinfo/numpy-discussion _______________________________________________ NumPy-Discussion mailing list [email protected] http://mail.scipy.org/mailman/listinfo/numpy-discussion
