arr.names
should have been arr.dtype.names
in that pack_last_axis
function
Eric
On Fri, Jan 26, 2018 at 10:48 AM, Allan Haldane <allanhaldane@gmail.com> wrote:> What do folks think about a totuple() method — even before this I’ve
> wanted that. But in this case, it seems particularly useful.Two thoughts:
1. `totuple` makes most sense for 2d arrays. But what should it do for
1d or 3+d arrays? I suppose it could make the last dimension a tuple, so
1d arrays would give a list of tuples of size 1.I was thinking it would be exactly like .tolist() but with tuples -- so you'd get tuples all the way down (or is that turtles?)IN this use case, it would have saved me the generator expression:(tuple(r) for r in arr)not a huge deal, but it would be nice to not have to write that, and to have the looping be in C with no intermediate array generation.2. structured array's .tolist() already returns a list of tuples. If we
have a 2d structured array, would it add one more layer of tuples?no -- why? it would return a tuple of tuples instead.That
would raise an exception if read back in by `np.array` with the same dtype.Hmm -- indeed, if the top-level structure is a tuple, the array constructor gets confused:This works fine -- as it should:
In [84]: new_full = np.array(full.tolist(), full.dtype)
But this does not:
In [85]: new_full = np.array(tuple(full.tolist()), full.dtype)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-85-c305063184ff> in <module>()
----> 1 new_full = np.array(tuple(full.tolist()), full.dtype)
ValueError: could not assign tuple of length 4 to structure with 2 fields.
I was hoping it would dig down to the inner structures looking for a match to the dtype, rather than looking at the type of the top level. Oh well.So yeah, not sure where you would go from tuple to list -- probably at the bottom level, but that may not always be unambiguous.These points make me think that instead of a `.totuple` method, this
might be more suitable as a new function in np.lib.recfunctions.I don't seem to have that module -- and I'm running 1.14.0 -- is this a new idea?If the
goal is to help manipulate structured arrays, that submodule is
appropriate since it already has other functions do manipulate fields in
similar ways. What about calling it `pack_last_axis`?
def pack_last_axis(arr, names=None):
if arr.names:
return arr
names = names or ['f{}'.format(i) for i in range(arr.shape[-1])]
return arr.view([(n, arr.dtype) for n in names]).squeeze(-1)
Then you could do:
>>> pack_last_axis(uv).tolist()
to get a list of tuples.not sure what idea is here -- in my example, I had a regular 2-d array, so no names:In [90]: pack_last_axis(uv)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-90-a75ee44c8401> in <module>()
----> 1 pack_last_axis(uv)
<ipython-input-89-cfbc76779d1f> in pack_last_axis(arr, names)
1 def pack_last_axis(arr, names=None):
----> 2 if arr.names:
3 return arr
4 names = names or ['f{}'.format(i) for i in range(arr.shape[-1])]
5 return arr.view([(n, arr.dtype) for n in names]).squeeze(-1)
AttributeError: 'numpy.ndarray' object has no attribute 'names'
So maybe you meants something like:
In [95]: def pack_last_axis(arr, names=None):
...: try:
...: arr.names
...: return arr
...: except AttributeError:
...: names = names or ['f{}'.format(i) for i in range(arr.shape[-1])]
...: return arr.view([(n, arr.dtype) for n in names]).squeeze(-1)
which does work, but seems like a convoluted way to get tuples!However, I didn't actually need tuples, I needed something I could pack into a stuctarray, and this does work, without the tolist:full = np.array(zip(time, pack_last_axis(uv)), dtype=dt)
So maybe that is the way to go.
I'm not sure I'd have thought to look for this function, but what can you do?Thanks for your attention to this,-CHB--
Christopher Barker, Ph.D.
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