[Numpy-discussion] Syntax Improvement for Array Transpose

[Charles R Harris]

On Wed, Jun 26, 2019 at 2:18 PM Ralf Gommers <ralf.gommers at gmail.com> wrote:

>
>
> On Wed, Jun 26, 2019 at 10:04 PM Kirill Balunov <kirillbalunov at gmail.com>
> wrote:
>
>> Only concerns #4 from Ilhan's list.
>>
>> ср, 26 июн. 2019 г. в 00:01, Ralf Gommers <ralf.gommers at gmail.com>:
>>
>>>
>>> [....]
>>>
>>> Perhaps not full consensus between the many people with different
>>> opinions and interests. But for the first one, arr.T change: it's clear
>>> that this won't happen.
>>>
>>
>> To begin with, I must admit that I am not familiar with the accepted
>> policy of introducing changes to NumPy. But I find it quite
>> nonconstructive just to say - it will not happen. What then is the point
>> in the discussion?
>>
>
> There has been a *very* long discussion already, and several others on the
> same topic before. There are also long-standing ways of dealing with
> backwards compatibility - e.g. what Matthew said is not new, it's an agreed
> upon way of working.
> http://www.numpy.org/neps/nep-0023-backwards-compatibility.html lists
> some principles. That NEP is not yet accepted (it needs rework), but it
> gives a good idea of what does and does not go.
>
>
>>
>>
>>> Between Juan's examples of valid use, and what Stephan and Matthew said,
>>> there's not much more to add. We're not going to change correct code for
>>> minor benefits.
>>>
>>
>> I fully agree that any feature can find its use, valid or not is another
>> question. Juan did not present these examples, but I will allow myself
>> to assume that it is more correct to describe what is being done there as a
>> permutation, and not a transpose. In addition, in the very next
>> sentence, Juan adds that "These could be easily changed to .transpose()
>> (honestly they probably should!)"
>>
>> We're not going to change correct code for minor benefits.
>>>
>>
>> It's fair, I personally have no preferences in both cases, the most
>> important thing for me is that in the 2d case it works correctly. To be
>> honest, until today, I thought that `.T` will raise for` ndim > 2`. At
>> least that's what my experience told me. For example in
>>
>>     Matlab - Error using  .' Transpose on ND array is not defined. Use
>> PERMUTE instead.
>>
>>     Julia - transpose not defined for Array(Float64, 3). Consider using
>> permutedims for higher-dimensional arrays.
>>
>>     Sympy - raise ValueError("array rank not 2")
>>
>> Here, I agree with the authors that, to begin with, `transpose` is not
>> the best name, since in general it doesn’t fit as an any mathematical
>> definition (of course it will depend on what we take as an element) or a
>> definition from linear algebra. Thus the name `transpose` only leads to
>> confusion.
>>
>> For a note about another suggestion - `.T` to mean a transpose of the
>> last two dimensions, in Mathematica authors for some reason did the
>> opposite (personally, I could not understand why they made such a choice
>> :) ):
>>
>>     Transpose[list]
>>         transposes the first two levels in list.
>>
>>     I feel strongly that we should have the following policy:
>>>
>>>     * Under no circumstances should we make changes that mean that
>>> correct
>>>     old code will give different results with new Numpy.
>>>
>>
>> I find this overly strict rules that do not allow to evolve. I
>> completely agree that a silent change in behavior is a disaster, that
>> changing behavior (if it is not an error) in the same minor version (1.X.Y)
>> is not acceptable, but I see no reason to extend this rule for a major
>> version bump (2.A.B.),  especially if it allows something to improve.
>>
>
> I'm sorry, you'll have to live with this rule. We've had lots of
> discussion about this rule in many concrete cases. When existing code is
> buggy or is consistently confusing many users, we can discuss. But in
> general changing old code to do something else is a terrible idea.
>
>
>> I would see such a rough version of a roadmap of change (I foresee my
>> loneliness in this :)) Also considering this comment
>>
>>     Personally I would find any divergence between a.T and a.transpose()
>>>     to be rather surprising.
>>>
>>
>> it will be as follows:
>>
>> 1. in 1.18 add the `.permute` method to the array, with the same
>> semantics as `.transpose`.
>> 2. Starting from 1.18, emit  `FutureWarning`, ` DeprectationWarning` for
>> `.transpose` and advise replacing it with `.permute`.
>> 3. Starting from 1.18 for `.T` with` ndim> 2`, emit a `FutureWarning`,
>> with a note that in future versions the behavior will change.
>> 4. In version 2, remove the `.transpose` and change the behavior for `.T`.
>>
>
> This is simply not enough. Many users will skip versions when upgrading.
> There must be an exceptionally good reason to change numerical results, and
> this simply is not one.
>
>
I agree with Ralf that `*.T` should be left alone, it is widely used and
changing its behavior is bound to lead to broken code. I could see `*.mT`
or `*.mH`, but I'm beginning to wonder if we would not be better served
with a better matrix class that could also deal intelligently with stacks
of row and column vectors. In the past I have preferred `einsum` over `@`
precisely because it made handling those variations easy. The `@` operator
is very convenient at a low level, but it simply cannot deal with stacks of
mixed types in generality. With a class we could do something about that.

 Chuck
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