[Numpy-discussion] ndrange, like range but multidimensiontal

[Mark Harfouche]

Eric, interesting ideas.

> __getitem__(Tuple[int]) which returns numpy scalars

I'm not sure what you mean. Even if you supply a numpy uint8 to range, it
still returns a python int class.
Would you like ndrange to return a tuple of `uint8` in this case?

```
In [3]: a =
iter(range(np.uint8(10)))

In [4]:
next(a).__class__
Out[4]: int

In [5]:
np.uint8(10).__class__
Out[5]: numpy.uint8
```

Ravel seems like a cool way to choose iteration order. In the PR, I
mentionned that one reason that I removed `'F'` order from the PR was:
1. My implementation was not competitive with the `C` order implementation
in terms of speed (can be fixed)
2. I don't know if it something that people really need to iterate over
collections (annoying to maintain if unused)

Instead, I just showed an example how people could iterate in `F` order
should they need to.

I'm not sure if we ever want the `ndrange` object to return a full matrix.
It seems like we would be creating a custom tuple class just for this which
seems pretty niche.


On Thu, Oct 11, 2018 at 10:21 AM Eric Wieser <wieser.eric+numpy at gmail.com>
wrote:

> Isn’t that what arange is for?
>
> Imagining ourselves in python2 land for now - I’m proposing arange is to
> range, as ndrange is to xrange
>
> I’m not convinced it should return an ndarray
>
> I agree - I think it should return a range-like object that:
>
>    - Is convertible via __array__ if needed
>    - Looks like an ndarray, with:
>       - a .dtype attribute
>       - a __getitem__(Tuple[int]) which returns numpy scalars
>       - .ravel() and .flat for choosing iteration order.
>
> On Wed, 10 Oct 2018 at 11:21 Allan Haldane allanhaldane at gmail.com
> <http://mailto:allanhaldane@gmail.com> wrote:
>
> On 10/10/18 12:34 AM, Eric Wieser wrote:
>> > One thing that worries me here - in python, |range(...)| in essence
>> > generates a lazy |list| - so I’d expect |ndrange| to generate a lazy
>> > |ndarray|. In practice, that means it would be a duck-type defining an
>> > |__array__| method to evaluate it, and only implement methods already
>> > present in numpy.
>>
>> Isn't that what arange is for?
>>
>> It seems like there are two uses of python3's range: 1. creating a 1d
>> iterable of indices for use in for-loops, and 2. with list(range) can be
>> used to create a sequence of integers.
>>
>> Numpy can extend this in two directions:
>>  * ndrange returns an iterable of nd indices (for for-loops).
>>  * arange returns an 1d ndarray of integers instead of a list
>>
>> The application of for-loops, which is more niche, doesn't need
>> ndarray's vectorized properties, so I'm not convinced it should return
>> an ndarray. It certainly seems simpler not to return an ndarray, due to
>> the dtype question.
>>
>> arange on its own seems to cover the need for a vectorized version of
>> range.
>>
>> Allan
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