[Numpy-discussion] asanyarray vs. asarray

Eric Moore ewm at redtetrahedron.org
Tue Oct 30 08:14:38 EDT 2018


On Tue, Oct 30, 2018 at 12:49 AM Eric Wieser <wieser.eric+numpy at gmail.com>
wrote:

> The latter - changing the behavior of multiplication breaks the principle.
>
> But this is not the main reason for deprecating matrix - almost all of the
> problems I’ve seen have been caused by the way that matrices behave when
> sliced. The way that m[i][j] and m[i,j] are different is just one example
> of this, the fact that they must be 2d is another.
>
> Matrices behaving differently on multiplication isn’t super different in
> my mind to how string arrays fail to multiply at all.
>

The difference is that string arrays are not numeric.  This is an issue
since people want to pass a matrix Into places that want to multiple
element wise but that then breaks that code unless special provisions are
taken.  Numerical codes don’t work on string arrays anyway.

Eric





Eric
>
> On Mon, 29 Oct 2018 at 20:54 Ralf Gommers <ralf.gommers at gmail.com> wrote:
>
> On Mon, Oct 29, 2018 at 4:31 PM Chris Barker <chris.barker at noaa.gov>
>> wrote:
>>
>>> On Fri, Oct 26, 2018 at 7:12 PM, Travis Oliphant <teoliphant at gmail.com>
>>> wrote:
>>>
>>>
>>>>  agree that we can stop bashing subclasses in general.   The problem
>>>> with numpy subclasses is that they were made without adherence to SOLID:
>>>> https://en.wikipedia.org/wiki/SOLID.  In particular the Liskov
>>>> substitution principle:
>>>> https://en.wikipedia.org/wiki/Liskov_substitution_principle .
>>>>
>>>
>>> ...
>>>
>>>
>>>> did not properly apply them in creating np.matrix which clearly
>>>> violates the substitution principle.
>>>>
>>>
>>> So -- could a matrix subclass be made "properly"? or is that an example
>>> of something that should not have been a subclass?
>>>
>>
>> The latter - changing the behavior of multiplication breaks the principle.
>>
>> Ralf
>>
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