On Tue, Jun 29, 2010 at 8:21 PM, Lisandro Dalcin wrote:
> Do we really need this for NumPy 2? What about using the old PyCObject
> for all Py 2.x versions? If this is not done, perhaps NumPy 2 on top
> of Py 2.x should still accept the __array_struct__ being a PyCObject?
>
> As reference, Cython
I didn't find these documented anywhere, I have numpy(couple day old
snapshot) install on python 2.7 OSX 64bit.
Thanks
Vincent
==
FAIL: test_print.test_complex_types(,)
Check formatting of complex types.
--
On Tue, Jun 29, 2010 at 8:16 PM, Bruce Southey wrote:
> On Tue, Jun 29, 2010 at 6:03 PM, David Goldsmith
> wrote:
> > On Tue, Jun 29, 2010 at 3:56 PM, wrote:
> >>
> >> On Tue, Jun 29, 2010 at 6:37 PM, David Goldsmith
> >> wrote:
> >> > ...concerns the behavior of numpy.random.multivariate_norm
On Tue, Jun 29, 2010 at 6:03 PM, David Goldsmith
wrote:
> On Tue, Jun 29, 2010 at 3:56 PM, wrote:
>>
>> On Tue, Jun 29, 2010 at 6:37 PM, David Goldsmith
>> wrote:
>> > ...concerns the behavior of numpy.random.multivariate_normal; if that's
>> > of
>> > interest to you, I urge you to take a look
OK, now I understand: dtype(out) is preserved, whatever that happens to be,
not dtype(a) (which is what I thought it meant) - I better clarify. Thanks!
DG
On Tue, Jun 29, 2010 at 7:28 PM, Skipper Seabold wrote:
> On Tue, Jun 29, 2010 at 8:50 PM, David Goldsmith
> wrote:
> > Hi, folks. Under P
On Tue, Jun 29, 2010 at 8:50 PM, David Goldsmith
wrote:
> Hi, folks. Under Parameters, the docstring for numpy.core.fromnumeric.all
> says:
>
> "out : ndarray, optionalAlternative output array in which to place the
> result. It must have the same shape as the expected output and the type is
> pre
Do we really need this for NumPy 2? What about using the old PyCObject
for all Py 2.x versions? If this is not done, perhaps NumPy 2 on top
of Py 2.x should still accept the __array_struct__ being a PyCObject?
As reference, Cython still uses PyCObject for Py<3.1
http://hg.cython.org/cython-devel/r
Hi, folks. Under Parameters, the docstring for numpy.core.fromnumeric.all
says:
"out : ndarray, optionalAlternative output array in which to place the
result. It must have the same shape as the expected output and *the type is
preserved*." [emphasis added].I assume this is a
copy-and-paste-from-a
On Tue, Jun 29, 2010 at 3:56 PM, wrote:
> On Tue, Jun 29, 2010 at 6:37 PM, David Goldsmith
> wrote:
> > ...concerns the behavior of numpy.random.multivariate_normal; if that's
> of
> > interest to you, I urge you to take a look at the comments (esp. mine :-)
> );
> > otherwise, please ignore the
On Tue, Jun 29, 2010 at 6:37 PM, David Goldsmith
wrote:
> ...concerns the behavior of numpy.random.multivariate_normal; if that's of
> interest to you, I urge you to take a look at the comments (esp. mine :-) );
> otherwise, please ignore the noise. Thanks!
You should add the link to the ticket,
...concerns the behavior of numpy.random.multivariate_normal; if that's of
interest to you, I urge you to take a look at the comments (esp. mine :-) );
otherwise, please ignore the noise. Thanks!
DG
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On Jun 29, 2010, at 1:41 PM, Martin Janousek wrote:
> Hi,
>
> I have a Python code working on MaskedArray which can produce arrays
> of a number of different shapes and ranks. In an extreme case I get
> "an array" constructed from a scalar:
>
> x=numpy.ma.array(333.,mask=False)
>
> Until the r
Hi,
I have a Python code working on MaskedArray which can produce arrays
of a number of different shapes and ranks. In an extreme case I get
"an array" constructed from a scalar:
x=numpy.ma.array(333.,mask=False)
Until the recent upgrade to Numpy 1.4.1 it has been possible to do
operations on su
Steven G. Johnson wrote:
>> Regarding constraints, the suggestion was to "manually" substitute my
>> variables with combinations of exp()-expressions that would implicitly
>> take care of the r_i>0 and 0> Question: Does NLopt allow to do those optimizations in a more direct,
>> less "manual" and s
Sebastian Haase wrote:
> this sounds like the library I was looking for.
> Would you mind reading my post
> [SciPy-User] Global Curve Fitting of 2 functions to 2 sets of
> data-curves
> http://mail.scipy.org/pipermail/scipy-user/2010-June/025674.html
> ?
> I got many interesting answ
Sebastian Haase wrote:
> this sounds like the library I was looking for.
> Would you mind reading my post
> [SciPy-User] Global Curve Fitting of 2 functions to 2 sets of data-curves
> http://mail.scipy.org/pipermail/scipy-user/2010-June/025674.html
> ?
> I got many interesting answers, where appare
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