If all the SSL certification updates have been done properly, this message
should go through.
-- Didrik
On 14 September 2016 at 13:00, Didrik Pinte wrote:
> Hi everyone,
>
> While updating the scipy SSL certificates yesterday, it appeared that
> filesystem of the servers is corrupted (more than
I have put a pull request implementing numpy.guvectorize up for review:
https://github.com/numpy/numpy/pull/8054
Cheers,
Stephan
On Tue, Sep 13, 2016 at 10:54 PM, Travis Oliphant
wrote:
> There has been some discussion on the Numba mailing list as well about a
> version of guvectorize that does
On Mon, Sep 26, 2016 at 10:20 PM, Didrik Pinte wrote:
> If all the SSL certification updates have been done properly, this message
> should go through.
>
It did, thanks Didrik!
Ralf
>
> -- Didrik
>
> On 14 September 2016 at 13:00, Didrik Pinte wrote:
>
>> Hi everyone,
>>
>> While updating th
Testing if this gets posted... Chuck
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Hi
I am working on issue #7949, and need to use "-3" switch while running
python 2.7 for my tests.
python -3 -c "import numpy as np; np.test()"
Several errors are reported and all all of them are DeprecationWarnings,
which is ok. (https://travis-ci.org/njase/numpy/jobs/162733502)
*But now these
On Mo, 2016-09-26 at 15:36 +0200, Saurabh Mehta wrote:
> Hi
>
> I am working on issue #7949, and need to use "-3" switch while
> running python 2.7 for my tests.
> python -3 -c "import numpy as np; np.test()"
>
> Several errors are reported and all all of them are
> DeprecationWarnings, which is
Hey,
I have a file:
;Eintrittsdatum;;;
;04.03.16;;10,00 €;genehmigt
;04.03.16;;10,00 €;genehmigt
which I try to parse using
def dateToNumpyDate(s):
s = s.decode("utf-8")
ret = datetime.datetime.strptime(s, "%d.%m.%y").isoformat()
return ret
def generateMemb
Hello,
Pull Request: https://github.com/numpy/numpy/pull/8053
I would like to expose a tolerance parameter for the function
numpy.random.multinomial.
The function `multinomial(n, pvals, size=None)` correctly raises exception
when `sum(pvals) > 1 + 1e-12` as these values should sum to 1.
I would actually be just as happy to relax the tolerance here to 1e-8
always. I doubt this would catch any fewer bugs than the current default.
In contrast, adding new parameters adds cognitive overload for everyone
encountering the function.
Also, for your use case note that tensorflow has it's o