On Sat, Oct 4, 2008 at 11:14 AM, Daniel Wolff <[EMAIL PROTECTED]> wrote:
> Hello, I recently upgraded to python 2.6. I cannot seem to find the
> appropriate numpy install file. I tried to make use of the .exe built for
> python 2.5 but the installer hung. Any suggestions? Regards, Daniel
Hi Daniel
On Sat, Oct 4, 2008 at 13:14, Daniel Wolff <[EMAIL PROTECTED]> wrote:
> Hello, I recently upgraded to python 2.6. I cannot seem to find the
> appropriate numpy install file. I tried to make use of the .exe built for
> python 2.5 but the installer hung. Any suggestions? Regards, Daniel
Right, you c
Hello, I recently upgraded to python 2.6. I cannot seem to find the
appropriate numpy install file. I tried to make use of the .exe built for
python 2.5 but the installer hung. Any suggestions? Regards, Daniel
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On Sat, Oct 04, 2008 at 05:59:40PM +0200, Tiziano Zito wrote:
> Hi,
> > This seems to tell that numpy has been build without altas. Hum, maybe we
> > need to work with the Debian guys to make sure that numpy is available
> > with altas.
> we had recently a discussion regarding this issue on this
Ravi wrote:
> Hi,
> PyArray_New seems to return a fortran contiguous array regardless of the
> requested array type. I am using numpy version 1.1.1.
>
> PyObject *obj = PyArray_New( &PyArray_Type, 2, dims, /*whatever*/, NULL,
> NULL, 0, NPY_CARRAY, NULL );
> PyOb
Hi Travis,
The following turned up on the 64-bit windows buildbot. I don't know what
triggers them as they don't normally show, but they look legit.
numpy\core\src\ufuncobject.c(1700) : warning C4244: '=' : conversion
from 'npy_intp' to 'int', possible loss of data
numpy\core\src\ufuncobject.c(17
> Suppose I have a toeplitz matrix, A. There is a well known algorithm
> for computing the matrix vector product Ax, in NlogN operations. An
> exact reference escapes me, but it may be in Golub & van Loan's book.
>
> My question is, how could I best take advantage of this algorithm
> withi
Hi,
> This seems to tell that numpy has been build without altas. Hum, maybe we
> need to work with the Debian guys to make sure that numpy is available
> with altas.
>
we had recently a discussion regarding this issue on this mailinglist, see:
http://groups.google.com/group/Numpy-discussion/brow
Suppose I have a toeplitz matrix, A. There is a well known algorithm
for computing the matrix vector product Ax, in NlogN operations. An
exact reference escapes me, but it may be in Golub & van Loan's book.
My question is, how could I best take advantage of this algorithm
within numpy/scip
Hi,
PyArray_New seems to return a fortran contiguous array regardless of the
requested array type. I am using numpy version 1.1.1.
PyObject *obj = PyArray_New( &PyArray_Type, 2, dims, /*whatever*/, NULL,
NULL, 0, NPY_CARRAY, NULL );
PyObject *obj = PyArray_New(
Why does converting nan to an integer not throw an exception (as with
inf), instead numpy silently replaces nan by zero?
>>> inti = np.array([0,1,2])
>>> inti.dtype
dtype('int32')
>>> inti[1] = np.inf
Traceback (most recent call last):
File "", line 1, in ?
inti[1] = np.inf
OverflowError: c
On Fri, Oct 03, 2008 at 09:11:58PM +, Pauli Virtanen wrote:
> Fri, 03 Oct 2008 18:59:02 +0200, Gael Varoquaux wrote:
> > I am doing a calculation where one call numpy.dot ends up taking 90%
> > of
> > the time (the array is huge: (61373, 500) ).
> > Any chance I can make this faster? I would
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