Hi Toby,

 >> I was currently in the process of running Philippe's autotuner. So it
>> turned out that the installation process aborted because my stock
>> installation of NumPy (1.6.1) is outdated. My machine runs a Linux Mint
>> Maya, which is built on top of Ubuntu 12.04.
>
> Try changing lines 225 and 226 in setup.py so that the inequality is
> true for numpy 1.6. I haven't tried building against that, but it may
> well work.

Okay, I tried that in the meanwhile and compilation worked. How can I 
verify proper operation with tests?


>> Is there any chance we can also support such 'older' setups,
>> particularly as this is an LTS release and supported for a few more years?
>
> It depends on if boost-numpy supports older numpy, and if not, how much
> work it will be to modify it :)

Looks like everything is in good order compilation-wise :-)


>> Note: I'm not yet talking about Enterprise OSes like RedHat 5 (CentOS
>> 5), which are still in use at companies... We should make reasonable
>> efforts to also support such machines, not every user has the privilege
>> of root access and the time and will to manually install the latest
>> versions.
>
> It's easy to install Python packages locally. Just pass '--user' to
> `setup.py install`, or to `pip install`, whichever you are using. Though
> indeed, we should keep things as seamless as possible.
>
> Note that if you were running `pip install pyviennacl` -- as I expect
> most users to do -- and you didn't have a modern numpy installed, then
> pip would install one for you as a consequence of the dependency.

I'm just test-driving Philippe's autotuner, where this is part of the 
build process. Either way, thanks for the clarifications :-)

Best regards,
Karli


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