On Mar 7, 2007, at 04:57 , Lars Bittrich wrote:
On Monday 05 March 2007 08:01, Steffen Loeck wrote:
Has there been any progress in solving this problem? I get the
same error
message and have no idea how to solve it.
I do not understand those code parts very well but I think the
values pas
On Wednesday 07 March 2007 09:57, Lars Bittrich wrote:
> I do not understand those code parts very well but I think the values
> passed to the lapack routines must be integer and not long integer on 64bit
> architecture. A few tests with the attached patch worked well.
It works fine for me now.
T
Steffen Loeck wrote:
>Fernando Perez wrote:
>
>
>>I recently got a report of a bug triggered only on 64-bit hardware,
>>and on a machine (in case it's relevant) that runs python 2.5. This
>>is with current numpy SVN which I just rebuilt a moment ago to
>>triple-check:
>>
>>In [3]: a = numpy.arr
On Monday 05 March 2007 08:01, Steffen Loeck wrote:
> Has there been any progress in solving this problem? I get the same error
> message and have no idea how to solve it.
I do not understand those code parts very well but I think the values passed
to the lapack routines must be integer and not l
Steffen Loeck wrote:
> Fernando Perez wrote:
>
>> I recently got a report of a bug triggered only on 64-bit hardware,
>> and on a machine (in case it's relevant) that runs python 2.5. This
>> is with current numpy SVN which I just rebuilt a moment ago to
>> triple-check:
>>
>> In [3]: a = numpy
Fernando Perez wrote:
> I recently got a report of a bug triggered only on 64-bit hardware,
> and on a machine (in case it's relevant) that runs python 2.5. This
> is with current numpy SVN which I just rebuilt a moment ago to
> triple-check:
>
> In [3]: a = numpy.array([[1.0,2],[3,4]])
>
> In [4]
Hi all,
I recently got a report of a bug triggered only on 64-bit hardware,
and on a machine (in case it's relevant) that runs python 2.5. This
is with current numpy SVN which I just rebuilt a moment ago to
triple-check:
In [3]: a = numpy.array([[1.0,2],[3,4]])
In [4]: numpy.linalg.qr(a)
** On