On Thu, Nov 5, 2015 at 2:50 PM, Ralf Gommers wrote:
>
>
> On Wed, Nov 4, 2015 at 8:28 PM, Charles R Harris <
> charlesr.har...@gmail.com> wrote:
>
>> Hi All,
>>
>> This is to open a discussion of a change of behavior of `np.allclose`.
>> That function uses `isclose` in numpy 1.10 with the result
allclose() needs to return a bool so that one can do "if np.allclose(foo,
bar) is True" or some such. The "good behavior" is for np.isclose() to
return a memmap, which still confuses the heck out of me, but I am not a
memmap expert.
On Thu, Nov 5, 2015 at 4:50 PM, Ralf Gommers wrote:
>
>
> On We
On Wed, Nov 4, 2015 at 8:28 PM, Charles R Harris
wrote:
> Hi All,
>
> This is to open a discussion of a change of behavior of `np.allclose`.
> That function uses `isclose` in numpy 1.10 with the result that array
> subtypes are preserved whereas before they were not. In particular, memmaps
> are
Yup, https://github.com/numpy/numpy/issues/6196
On Wed, Nov 4, 2015 at 1:45 PM, Charles R Harris
wrote:
>
>
> On Wed, Nov 4, 2015 at 12:42 PM, Nathan Goldbaum
> wrote:
>
>> Oh oops, this is about np.allcose, not np.assert_allclose. Sorry for the
>> noise...
>>
>
> Probably related ;) Did you op
On Wed, Nov 4, 2015 at 12:42 PM, Nathan Goldbaum
wrote:
> Oh oops, this is about np.allcose, not np.assert_allclose. Sorry for the
> noise...
>
Probably related ;) Did you open an issue for it?
Chuck
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On Wed, Nov 4, 2015 at 12:40 PM, Benjamin Root wrote:
> I am not sure I understand what you mean. Specifically that np.isclose
> will return a memmap if one of the inputs is a memmap. The result is a
> brand new array, right? So, what is that result memmapping from? Also, how
> does this impact n
Oh oops, this is about np.allcose, not np.assert_allclose. Sorry for the
noise...
On Wed, Nov 4, 2015 at 1:36 PM, Nathan Goldbaum
wrote:
> I actually brought this up before 1.10 came out:
> https://github.com/numpy/numpy/issues/6196
>
> The behavior change brought out a bug in our use of allclos
I am not sure I understand what you mean. Specifically that np.isclose will
return a memmap if one of the inputs is a memmap. The result is a brand new
array, right? So, what is that result memmapping from? Also, how does this
impact np.allclose()? That function returns a scalar True/False, so what
I actually brought this up before 1.10 came out:
https://github.com/numpy/numpy/issues/6196
The behavior change brought out a bug in our use of allclose, so while it
was annoying in the sense that our test suite started failing in a new way,
it was good in that our tests are now more correct.
On
Hi All,
This is to open a discussion of a change of behavior of `np.allclose`. That
function uses `isclose` in numpy 1.10 with the result that array subtypes
are preserved whereas before they were not. In particular, memmaps are
returned when at least one of the inputs is a memmap. By and large I
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