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+nu...@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 allanhald...@gmail.com > <http://mailto:allanhald...@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 >> _______________________________________________ >> NumPy-Discussion mailing list >> NumPy-Discussion@python.org >> https://mail.python.org/mailman/listinfo/numpy-discussion >> > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@python.org > https://mail.python.org/mailman/listinfo/numpy-discussion >
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