[Numpy-discussion] what would you expect A[none] to do?

[Neal Becker]

In my case, what it does is:

A.shape = (5760,)
A[none] -> (1, 5760)

In my case, use of none here is just a mistake. But why would you want this
to be accepted at all, and how should it be interpreted?

[Neal Becker]

Post by Neal Becker
A.shape = (5760,)
A[none] -> (1, 5760)
In my case, use of none here is just a mistake. But why would you want
this to be accepted at all, and how should it be interpreted?

Actually, in my particular case, if it just acted as a noop, returning the
original array, that would have been perfect. No idea if that's a good
result in general.

[Sebastian Berg]

Post by Neal Becker

Post by Neal Becker
A.shape = (5760,)
A[none] -> (1, 5760)
In my case, use of none here is just a mistake. But why would you want
this to be accepted at all, and how should it be interpreted?

Actually, in my particular case, if it just acted as a noop,
returning the
original array, that would have been perfect. No idea if that's a good
result in general.

We have `np.newaxis` with `np.newaxis is None` for the same thing.
`None` inserts a new axes, it is documented to do so in the indexing
documentation, so I will ask you to check it if you have more
questions.
If you want a noop, you should probably use `...` or `Ellipsis`.


- Sebastian

Post by Neal Becker
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[Joe Kington]

Slicing with None adds a new dimension. It's a common paradigm, though
usually you'd use A[np.newaxis] or A[np.newaxis, ...] instead for
readibility. (np.newaxis is None, but it's a lot more readable)

There's a good argument to be made that slicing with a single None
shouldn't add a new axis, and only the more readable forms like A[None, :],
A[..., None], etc should.

However, that would rather seriously break backwards compatibility. There's
a fair amount of existing code that assumes "A[None]" prepends a new axis.

Post by Neal Becker

Post by Neal Becker
A.shape = (5760,)
A[none] -> (1, 5760)
In my case, use of none here is just a mistake. But why would you want
this to be accepted at all, and how should it be interpreted?

Actually, in my particular case, if it just acted as a noop, returning the
original array, that would have been perfect. No idea if that's a good
result in general.
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NumPy-Discussion mailing list
https://mail.scipy.org/mailman/listinfo/numpy-discussion

[Benjamin Root]

TBH, I wouldn't have expected it to work, but now that I see it, it does
make some sense. I would have thought that it would error out as being
ambiguous (prepend? append?). I have always used ellipses to make it
explicit where the new axis should go. But, thinking in terms of how
regular indexing works, I guess it isn't all that ambiguous.

Ben Root

Post by Joe Kington
Slicing with None adds a new dimension. It's a common paradigm, though
usually you'd use A[np.newaxis] or A[np.newaxis, ...] instead for
readibility. (np.newaxis is None, but it's a lot more readable)
There's a good argument to be made that slicing with a single None
shouldn't add a new axis, and only the more readable forms like A[None, :],
A[..., None], etc should.
However, that would rather seriously break backwards compatibility.
There's a fair amount of existing code that assumes "A[None]" prepends a
new axis.

Post by Neal Becker

Post by Neal Becker
A.shape = (5760,)
A[none] -> (1, 5760)
In my case, use of none here is just a mistake. But why would you want
this to be accepted at all, and how should it be interpreted?

Actually, in my particular case, if it just acted as a noop, returning the
original array, that would have been perfect. No idea if that's a good
result in general.
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https://mail.scipy.org/mailman/listinfo/numpy-discussion

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[Nathaniel Smith]

Post by Benjamin Root
TBH, I wouldn't have expected it to work, but now that I see it, it does
make some sense. I would have thought that it would error out as being
ambiguous (prepend? append?). I have always used ellipses to make it
explicit where the new axis should go. But, thinking in terms of how regular
indexing works, I guess it isn't all that ambiguous.

Yeah, I'm not really a fan of the rule that indexing with too-few axes
implicitly adds a "..." on the right

A[0] -> A[0, ...]

but given that we do have that rule, then A[None] -> A[None, ...] does
make sense.

-n