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
On 3/7/07, Daniel Mahler <[EMAIL PROTECTED]> wrote:
My problem is not space, but time.
I am creating a small array over and over,
and this is turning out to be a bottleneck.
My experiments suggest that problem is the allocation,
not the random number generation.
Allocating all the arrays as one
> > My problem is not space, but time.
> > I am creating a small array over and over,
> > and this is turning out to be a bottleneck.
How about making one large random number array and taking small views?
Matthew
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On 07/03/07, Daniel Mahler <[EMAIL PROTECTED]> wrote:
> My problem is not space, but time.
> I am creating a small array over and over,
> and this is turning out to be a bottleneck.
> My experiments suggest that problem is the allocation,
> not the random number generation.
> Allocating all the arr
My problem is not space, but time.
I am creating a small array over and over,
and this is turning out to be a bottleneck.
My experiments suggest that problem is the allocation,
not the random number generation.
Allocating all the arrays as one n+1 dim and grabbing rows from it
is faster than alloc
On 3/7/07, Matthew Koichi Grimes <[EMAIL PROTECTED]> wrote:
I would like to twiddle with the strides of a matrix such that the rows
overlap each other. I've gotten this far:
In [1]: import numpy as N
In [2]: mat = N.arange(12).reshape(3,4)
In [3]: mat
Out[3]:
array([[ 0, 1, 2, 3],
[
I would like to twiddle with the strides of a matrix such that the rows
overlap each other. I've gotten this far:
In [1]: import numpy as N
In [2]: mat = N.arange(12).reshape(3,4)
In [3]: mat
Out[3]:
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]])
In [4]: mat.strides
On 3/7/07, Robert Kern <[EMAIL PROTECTED]> wrote:
Daniel Mahler wrote:
> Is there an efficient way to fill an existing array with random
> numbers without allocating a new array?
No, sorry.
There is however an only moderately inefficient way if you are primarily
concerned with keeping your t
Daniel Mahler wrote:
> Is there an efficient way to fill an existing array with random
> numbers without allocating a new array?
No, sorry.
--
Robert Kern
"I have come to believe that the whole world is an enigma, a harmless enigma
that is made terrible by our own mad attempt to interpret it a
Is there an efficient way to fill an existing array with random
numbers without allocating a new array?
thanks
Daniel
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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
Hi,
I am building numpy on a bunch of different systems right now and for
the most part I am always successful. Today though, I found a wierd
problem. Here is the traceback from doing python setup.py (below):
This is on an intel 10.4 box with no fortran compiler installed.
Incidently, after goo
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
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