Hi All,
I've been looking to implement the "@" operator from Python 3.5. Looking at
the current implementation of the dot function, it only uses a vector inner
product, which is either that defined in arraytypes.c.src or a version
using cblas defined in _dotblas for the float, cfloat, double, cdou
Hi,
On Tue, Aug 5, 2014 at 2:27 PM, Matthew Brett wrote:
> Hi,
>
> On Tue, Aug 5, 2014 at 1:57 PM, Julian Taylor
> wrote:
>> On 05.08.2014 22:32, Christoph Gohlke wrote:
>>> On 8/5/2014 12:45 PM, Julian Taylor wrote:
Hello,
I am pleased to announce the first release candidate for
On 5 Aug 2014, at 11:27 pm, Matthew Brett wrote:
> OSX wheels built and tested and uploaded OK :
>
> http://wheels.scikit-image.org
>
> https://travis-ci.org/matthew-brett/numpy-atlas-binaries/builds/31747958
>
> Will test against the scipy stack later on today.
Built and tested against the F
Hi,
On Tue, Aug 5, 2014 at 1:57 PM, Julian Taylor
wrote:
> On 05.08.2014 22:32, Christoph Gohlke wrote:
>> On 8/5/2014 12:45 PM, Julian Taylor wrote:
>>> Hello,
>>>
>>> I am pleased to announce the first release candidate for numpy 1.8.2, a
>>> pure bugfix release for the 1.8.x series.
>>> https:
On 05.08.2014 22:32, Christoph Gohlke wrote:
> On 8/5/2014 12:45 PM, Julian Taylor wrote:
>> Hello,
>>
>> I am pleased to announce the first release candidate for numpy 1.8.2, a
>> pure bugfix release for the 1.8.x series.
>> https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/
>>
>> If no
On 8/5/2014 12:45 PM, Julian Taylor wrote:
> Hello,
>
> I am pleased to announce the first release candidate for numpy 1.8.2, a
> pure bugfix release for the 1.8.x series.
> https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/
>
> If no regressions show up the final release is planned this
Hello,
I am pleased to announce the first release candidate for numpy 1.8.2, a
pure bugfix release for the 1.8.x series.
https://sourceforge.net/projects/numpy/files/NumPy/1.8.2rc1/
If no regressions show up the final release is planned this weekend.
The upgrade is recommended for all users of th
ah yes, that may indeed be what you want. depending on your datatype, you
could access the underlying raw data as a string.
b.tostring() in a.tostring() sort of works; but isn't entirely safe, as you
may have false positive matches which arnt aligned to your datatype
using str.find in combination
On Di, 2014-08-05 at 14:58 +0200, Jurgens de Bruin wrote:
> Hi,
>
> I am new to numpy so any help would be greatly appreciated.
>
> I have two arrays:
>
> array1 = np.arange(1,100+1)
> array2 = np.arange(1,50+1)
>
> How can I calculate/determine if array2 is a subset of array1 (falls
>
np.all(np.in1d(array1,array2))
On Tue, Aug 5, 2014 at 2:58 PM, Jurgens de Bruin
wrote:
> Hi,
>
> I am new to numpy so any help would be greatly appreciated.
>
> I have two arrays:
>
> array1 = np.arange(1,100+1)
> array2 = np.arange(1,50+1)
>
> How can I calculate/determine if array2 is
On Tue, Aug 5, 2014 at 1:58 PM, Jurgens de Bruin wrote:
> Hi,
>
> I am new to numpy so any help would be greatly appreciated.
>
> I have two arrays:
>
> array1 = np.arange(1,100+1)
> array2 = np.arange(1,50+1)
>
> How can I calculate/determine if array2 is a subset of array1 (falls within
Hi,
I am new to numpy so any help would be greatly appreciated.
I have two arrays:
array1 = np.arange(1,100+1)
array2 = np.arange(1,50+1)
How can I calculate/determine if array2 is a subset of array1 (falls within
array 1)
Something like : array2 in array1 = TRUE for the case above.
T
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