[Numpy-discussion] Why is the shape of a singleton array the empty tuple?
Sun Mar 7 01:04:19 CST 2010
On Sat, Mar 6, 2010 at 10:26 PM, Ian Mallett <email@example.com> wrote:
> On Sat, Mar 6, 2010 at 9:46 PM, David Goldsmith <firstname.lastname@example.org>wrote:
>> Thanks, Ian. I already figured out how to make it not so, but I still
>> want to understand the design reasoning behind it being so in the first
>> place (thus the use of the question "why (is it so)," not "how (to make it
> Well, I can't help you with that. I would also ask why this design even
> exists? Equating an array with a single number doesn't make sense to me.
Here's an (unintended) use case:
I wanted to convert anything in an array that's close to zero to be zero
(and leave the rest as is), but I want it to be robust so that if it
receives a scalar, it can work w/ that, too.
Here's my (working) code (I'm sure that once Robert sees it, he'll be able
to replace it w/ a one-liner):
arg = N.array(arg)
if not arg.shape:
arg = N.array((arg,))
t = N.array([0 if N.allclose(temp, 0) else temp for temp in arg])
if len(t.shape) - 1:
At first I wasn't "casting" arg to be an array upon entry, but I found that
if arg is a scalar, my list comprehension failed, so I had choose _some_
sort of sequence to cast scalars to; since arg will typically be an array
and that's what I wanted to return as well, it seemed most appropriate to
"cast" incoming scalars to arrays. So I added the arg = N.array(arg) at the
beginning (N.array(array) = array, and N.array(non-array seq) does the
"right" thing as well), but the list comprehension still wouldn't work if
arg was a scalar upon entry; after many print statements and much
interactive experimenting, I finally figured out that this is because the
shape of N.array(scalar) is () (and I thence immediately guessed, correctly
of course, that N.array((scalar,)) has shape (1,)). So I added the if not
arg.shape: to detect and correct for those zero size arrays, and now it
works fine, but I'd still like to know _why_ N.array(scalar).shape == () but
N.array((scalar,)).shape == (1,). No biggy, just curious.
-------------- next part --------------
An HTML attachment was scrubbed...
More information about the NumPy-Discussion