On Tue, 22 Sep 2015 04:43:18 -0500
Travis Oliphant wrote:
> Absolutely it would be good if others can test. All I was suggesting is
> that we do run a pretty decent set of tests upon build and that would be
> helpful.
>
> If the numpy build recipes are not available, it is only because they have
Absolutely it would be good if others can test. All I was suggesting is
that we do run a pretty decent set of tests upon build and that would be
helpful.
If the numpy build recipes are not available, it is only because they have
not been updated to use conda-build yet. If somebody wants to volun
On Sep 21, 2015 11:51 PM, "Travis Oliphant" wrote:
>
> Of course it will be 1.10.0 final where all the problems will show up
suddenly :-)
>
> Perhaps we can get to where we are testing Anaconda against beta releases
better.
The most useful thing would actually not even involve you doing any more
Of course it will be 1.10.0 final where all the problems will show up
suddenly :-)
Perhaps we can get to where we are testing Anaconda against beta releases
better.
-Travis
On Mon, Sep 21, 2015 at 5:19 PM, Charles R Harris wrote:
> Hi All,
>
> Just a heads up. The lack of reported problems in
Hi All,
Just a heads up. The lack of reported problems in 1.10.0b1 has been
stunning.
Chuck
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The reason why we don't have that extra slice is because we may not know
ahead of time that we are dealing with a 2D array. It could be a 1D array.
I guess we could use ellipses, but I wanted to make sure that the numpy
devs consider the above to be perfectly valid semantics because it is
entrenche
On Do, 2015-08-27 at 11:15 -0400, Benjamin Root wrote:
> Ok, I just wanted to make sure I understood the issue before going bug
> hunting. Chances are, it has been a bug on our end for a while now.
> Just to make sure, is the following valid?
>
>
> arr = np.zeros((5, 3))
>
> ind = np.array([True
Ok, I just wanted to make sure I understood the issue before going bug
hunting. Chances are, it has been a bug on our end for a while now. Just to
make sure, is the following valid?
arr = np.zeros((5, 3))
ind = np.array([True, True, True, False, True])
arr[ind] # gives a 4x3 result
Running that
On Do, 2015-08-27 at 08:04 -0600, Charles R Harris wrote:
>
>
> On Thu, Aug 27, 2015 at 7:52 AM, Benjamin Root
> wrote:
>
>
> Ok, I tested matplotlib master against numpy master, and there
> were no errors. I did get a bunch of new deprecation warnings
>
On Thu, Aug 27, 2015 at 7:52 AM, Benjamin Root wrote:
>
> Ok, I tested matplotlib master against numpy master, and there were no
> errors. I did get a bunch of new deprecation warnings though such as:
>
> "/nas/home/broot/centos6/lib/python2.7/site-packages/matplotlib-1.5.dev1-py2.7-linux-x86_64.
Ok, I tested matplotlib master against numpy master, and there were no
errors. I did get a bunch of new deprecation warnings though such as:
"/nas/home/broot/centos6/lib/python2.7/site-packages/matplotlib-1.5.dev1-py2.7-linux-x86_64.egg/matplotlib/colorbar.py:539:
VisibleDeprecationWarning: boolea
The change also seems to have made datetime64 computations stricter:
>>> np.datetime64('2010') - np.datetime64('2000-01-01')
numpy.timedelta64(3653,'D')
>>> np.datetime64('2010') - np.datetime64('2000-01-01T00:00:00Z')
Traceback (most recent call last):
File "", line 1, in
TypeError: Cannot c
Hi again,
The change seems to have possibly unforeseen consequences because some
ufuncs don't declare all possible types, e.g.:
>>> a = np.arange(10, dtype=np.int32)
>>> out = np.zeros_like(a)
>>> np.fabs(a, out=out)
Traceback (most recent call last):
File "", line 1, in
TypeError: ufunc 'fab
Aw, crap... I looked at the list of tags and saw the rc1... I'll test again
in the morning Grumble, grumble...
On Aug 26, 2015 10:53 PM, "Nathaniel Smith" wrote:
> On Aug 26, 2015 7:03 PM, "Benjamin Root" wrote:
> >
> > Just a data point, I just tested 1.9.0rc1 (built from source) with
> mat
On Aug 26, 2015 7:03 PM, "Benjamin Root" wrote:
>
> Just a data point, I just tested 1.9.0rc1 (built from source) with
matplotlib master, and things appear to be fine there. In fact, matplotlib
was built against 1.7.x (I was hunting down a regression), and worked
against the 1.9.0 install, so the
Just a data point, I just tested 1.9.0rc1 (built from source) with
matplotlib master, and things appear to be fine there. In fact, matplotlib
was built against 1.7.x (I was hunting down a regression), and worked
against the 1.9.0 install, so the ABI appears intact.
Cheers!
Ben Root
On Wed, Aug 26
On Wed, Aug 26, 2015 at 7:32 AM, Charles R Harris wrote:
>
>
> On Wed, Aug 26, 2015 at 7:31 AM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>>
>>
>> On Wed, Aug 26, 2015 at 7:11 AM, Antoine Pitrou
>> wrote:
>>
>>> On Tue, 25 Aug 2015 10:26:02 -0600
>>> Charles R Harris wrote:
>>> >
On Wed, Aug 26, 2015 at 7:11 AM, Antoine Pitrou wrote:
> On Tue, 25 Aug 2015 10:26:02 -0600
> Charles R Harris wrote:
> > Hi All,
> >
> > The silence after the 1.10 beta has been eerie. Consequently, I'm
> thinking
> > of making a first release candidate this weekend. If you haven't yet
> tested
On Wed, Aug 26, 2015 at 7:31 AM, Charles R Harris wrote:
>
>
> On Wed, Aug 26, 2015 at 7:11 AM, Antoine Pitrou
> wrote:
>
>> On Tue, 25 Aug 2015 10:26:02 -0600
>> Charles R Harris wrote:
>> > Hi All,
>> >
>> > The silence after the 1.10 beta has been eerie. Consequently, I'm
>> thinking
>> > of
On Tue, 25 Aug 2015 10:26:02 -0600
Charles R Harris wrote:
> Hi All,
>
> The silence after the 1.10 beta has been eerie. Consequently, I'm thinking
> of making a first release candidate this weekend. If you haven't yet tested
> the beta, please do so. It would be good to discover as many problems
Hi All,
The silence after the 1.10 beta has been eerie. Consequently, I'm thinking
of making a first release candidate this weekend. If you haven't yet tested
the beta, please do so. It would be good to discover as many problems as we
can before the first release.
Chuck
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