[Numpy-discussion] Setting custom dtypes and 1.14

[Eric Wieser]

Apologies, it seems that I skipped to the end of @ahaldane's remark - we're
on the same page.

On Fri, 26 Jan 2018 at 11:17 Eric Wieser <wieser.eric+numpy at gmail.com>
wrote:

> Why is the list of tuples a useful thing to have in the first place? If
> the goal is to convert an array into a structured array, you can do that
> far more efficiently with:
>
> def make_tup_dtype(arr):
>     """
>     Attempt to make a type capable of viewing the last axis of an array, even if it is non-contiguous.
>     Unfortunately `.view` doesn't allow us to use this dtype in that case, which needs a patch...
>     """
>     n_fields = arr.shape[-1]
>     step = arr.strides[-1]
>     descr = dict(names=[], formats=[], offsets=[], itemsize=step * n_fields)
>     for i in range(n_fields):
>         descr['names'].append('f{}'.format(i))
>         descr['offsets'].append(step * i)
>         descr['formats'].append(arr.dtype)
>     return np.dtype(descr)
>
> Used as:
>
> >>> arr = np.arange(6).reshape(3, 2)>>> arr.view(make_tup_dtype(arr)).squeeze(axis=-1)
> array([(0, 1), (2, 3), (4, 5)],
>       dtype=[('f0', '<i4'), ('f1', '<i4')])
>
> Perhaps this should be provided by recfunctions (or maybe it already is,
> in a less rigid form?)
>
> Eric
> ​
>
> On Fri, 26 Jan 2018 at 10:48 Allan Haldane <allanhaldane at gmail.com> wrote:
>
>> On 01/25/2018 08:53 PM, Chris Barker - NOAA Federal wrote:
>> >> On Jan 25, 2018, at 4:06 PM, Allan Haldane <allanhaldane at gmail.com>
>> wrote:
>> >
>> >>> 1) This is a known change with good reason?
>> >
>> >> . The
>> >> change occurred because the old assignment behavior was dangerous, and
>> >> was not doing what you thought.
>> >
>> > OK, that’s a good reason!
>> >
>> >>> A) improve the error message.
>> >>
>> >> Good idea. I'll see if we can do it for 1.14.1.
>> >
>> > What do folks think about a totuple() method — even before this I’ve
>> > wanted that. But in this case, it seems particularly useful.
>> >
>> > -CHB
>>
>> 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.
>>
>> 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? That
>> would raise an exception if read back in by `np.array` with the same
>> dtype.
>>
>> These points make me think that instead of a `.totuple` method, this
>> might be more suitable as a new function in np.lib.recfunctions. 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.
>>
>> Allan
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>>
>
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