Hey Guys,
I'm having the same problem with building a python wrapper for a C library
using windows.
Tried applying the patch mentioned above, but still receiving the following
error message.
Any thoughts?
Thanks
Mel
Looking for python34.dll
Building import library (arch=AMD64): "c:\Python34
On Wed, Dec 10, 2014 at 4:00 PM, Nathaniel Smith wrote:
> 2) Add a broadcast_to(arr, shape) function, which broadcasts the array
> to exactly the shape given, or else errors out if this is not
> possible.
>
I like np.broadcast_to as a new function. We can document it alongside
broadcast and broa
Chris Barker wrote:
> I haven't managed to trigger a segfault yet but it sure looks like I
> could...
You can also trigger random errors. If the array is small, Python's memory
mamager might keep the memory in the heap for reuse by PyMem_Malloc. And
then you can actually modify some random Pytho
On Sun, Dec 7, 2014 at 7:10 AM, Stephan Hoyer wrote:
> I recently wrote function to manually broadcast an ndarray to a given shape
> according to numpy's broadcasting rules (using strides):
> https://github.com/xray/xray/commit/7aee4a3ed2dfd3b9aff7f3c5c6c68d51df2e3ff3
>
> The same functionality ca
On Wed, Dec 10, 2014 at 8:26 PM, Valentin Haenel wrote:
> Hi,
>
> I am using numpy version 1.9.0 and Python 2.7.9 and have a question
> about the dtype:
>
> In [14]: np.dtype(" Out[14]: dtype('float64')
>
> In [15]: np.dtype(u" Out[15]: dtype('float64')
>
> In [16]: np.dtype([(" Out[16]: dtype([('
On Wed, Dec 10, 2014 at 9:03 PM, Chris Barker wrote:
> On Wed, Dec 10, 2014 at 11:44 AM, Andrea Gavana
> wrote:
>>
>> The argument is not check_refs, but refcheck.
>
> thanks -- yup, that works.
>
> Useful -- but dangerous!
>
> I haven't managed to trigger a segfault yet but it sure looks like I
On Wed, Dec 10, 2014 at 11:44 AM, Andrea Gavana
wrote:
> The argument is not check_refs, but refcheck.
>
thanks -- yup, that works.
Useful -- but dangerous!
I haven't managed to trigger a segfault yet but it sure looks like I
could...
-CHB
--
Christopher Barker, Ph.D.
Oceanographer
Eme
Dear Pierre,
thank you very much for your time to correct my notebook and to point me
in the direction of my wrong lag estimation. It has been very useful!
Best
Jose
On 09/12/14 17:23, Pierre Haessig wrote:
> Hi,
>
> Le 08/12/2014 22:02, Jose Guzman a écrit :
>> I'm trying to compute the cross
Hi,
I am using numpy version 1.9.0 and Python 2.7.9 and have a question
about the dtype:
In [14]: np.dtype(" in ()
> 1 np.dtype([(u" in ()
> 1 np.dtype([["http://mail.scipy.org/mailman/listinfo/numpy-discussion
On 10 December 2014 at 20:36, Chris Barker wrote:
> On Tue, Dec 9, 2014 at 11:03 PM, Sturla Molden
> wrote:
>
>> Nathaniel Smith wrote:
>>
>> > @contextmanager
>> > def tmp_zeros(*args, **kwargs):
>> > arr = np.zeros(*args, **kwargs)
>> > try:
>> > yield arr
>> > finally:
>>
The second argument is named `refcheck` rather than check_refs.
Eric
On Wed, Dec 10, 2014 at 2:36 PM, Chris Barker wrote:
> On Tue, Dec 9, 2014 at 11:03 PM, Sturla Molden
> wrote:
>
>> Nathaniel Smith wrote:
>>
>> > @contextmanager
>> > def tmp_zeros(*args, **kwargs):
>> > arr = np.zeros(
On Tue, Dec 9, 2014 at 11:03 PM, Sturla Molden
wrote:
> Nathaniel Smith wrote:
>
> > @contextmanager
> > def tmp_zeros(*args, **kwargs):
> > arr = np.zeros(*args, **kwargs)
> > try:
> > yield arr
> > finally:
> > arr.resize((0,), check_refs=False)
>
> That one is inte
-- Forwarded message --
From: "Bruno Cauet"
Date: 10 Dec 2014 17:07
Subject: [Python-Dev] Python 2.x and 3.x use survey, 2014 edition
To: ,
Cc: "Dan Stromberg"
Hi all,
Last year a survey was conducted on python 2 and 3 usage.
Here is the 2014 edition, slightly updated (from 9 to
On Mi, 2014-12-10 at 07:25 +, Sturla Molden wrote:
> Nathaniel Smith wrote:
>
> > This should be pretty trivial to implement. AFAICT you don't need any
> > complicated cython
>
> I have a bad habit of thinking in terms of too complicated C instead of
> just using NumPy.
>
>
> > @contextman
On Sun, Dec 7, 2014 at 11:31 PM, Pierre Haessig
wrote:
> Instead of putting this function in stride_tricks (which is quite
> hidden), could it be added instead as a boolean flag to the existing
> `reshape` method ? Something like:
>
> x.reshape(y.shape, broadcast=True)
>
> What other people think
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