[Numpy-discussion] Numerical Python and LAPACK on 64-bit machines

Paul F Dubois paul at pfdubois.com
Thu Mar 7 07:57:03 CST 2002


If someone is going to make the change they should change the source to
use FortranInt or some similar typedef so that one ifdef could be used
to change it.

I believe the current lapack/blas were made by an automatic conversion
tool. It is easy to make a case that they shouldn't even be in the
distribution, that rather a user should install their own library.
However, this is a problem on Windows, where many users do not have a
development environment, and in general, because it makes the
instructions for installing more complicated. So we have sort of felt
stuck with it.

I have no real way of convincing myself that the proposed change won't
break some other platform, although it seems unlikely. 

-----Original Message-----
From: numpy-discussion-admin at lists.sourceforge.net
[mailto:numpy-discussion-admin at lists.sourceforge.net] On Behalf Of Roman
Geus
Sent: Thursday, March 07, 2002 1:21 AM
To: numpy-discussion at lists.sourceforge.net
Subject: Re: [Numpy-discussion] Numerical Python and LAPACK on 64-bit
machines


Hello,

Pearu Peterson wrote:
> 
> Hi,
> 
> On Wed, 6 Mar 2002, Roman Geus wrote:
> 
> > So, what really needs to be changed (at least for this machine) is 
> > how Numerical Python calls BLAS/LAPACK. It also needs to use 32bit 
> > integers. So this means using 'int' instead of 'long int'.
> 
> Having wrapped a lot of Fortran codes to Python, I agree, that 
> Numerical Python should use 'int' instead of, 'long'. Though I have 
> little influence to make this change to happen in Numeric but just 
> agreeing with you.
> 
> Pearu

What would be the best way to convince the NumPy developers to use 'int'
instead 'long' for Fortran integers?

I would be willing to help making the necessary changes.

-- Roman

_______________________________________________
Numpy-discussion mailing list Numpy-discussion at lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/numpy-discussion





More information about the Numpy-discussion mailing list