Only concerns #4 from Ilhan's list. ср, 26 июн. 2019 г. в 00:01, Ralf Gommers <ralf.gommers@gmail.com>:
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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?
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 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`. Regarding `.T` with` ndim> 2` - I don’t have preferences between error or transpose of the last two dimensions. with kind regards, -gdg