On 10/22/06, Albert Strasheim <fu...@gm...> wrote:
>
> Hello all
>
> I'm trying to sort an array with two fields, but I'm getting a result that
> doesn't seem to make sense.
>
> What I tried (first attempt): I have two 2-D arrays. I would like to sort
> one based on the sort of the other. I managed to do this with argsort.
> However, the fancy indexing required to get the sorted array using what
> argsort returned was very slow. I followed this example:
It is certainly awkward. I am going to add a function to do this after
1.0comes out. Sounds like you need it now.
http://www.scipy.org/Numpy_Example_List#head-9f8656795227e3c43e849c6c0435eee
> b32afd722
>
> What I tried (second attempt): I created an array with two fields. I
> think/hope/expected that sorting the array would sort it on the first
> field
> in the dtype and then on the second. This is *much* faster than the fancy
> indexing approach.
I believe it sorts on the two fields together as one big binary blob.
<snip>
Output on my system:
>
> 1.0.dev3376
>
> before sort:
> [[(1.0, 1) (2.0, 2)]
> [(3.0, 3) (4.0, 4)]]
>
> after sort:
> [[(2.0, 2) (1.0, 1)]
> [(4.0, 4) (3.0, 3)]]
>
> The already sorted array has been unsorted in some way. Any thoughts?
I suspect something to do with the binary representation of the floats.
Probably depends on big/little endian also. The floats 1.0, 2.0, and
4.0all have zero mantissas while
3.0 has a one. The sort behaves differently if uint8 is used for both
fields.
In [3]: dt = dtype([('aaa', uint8), ('bbb', uint8)])
In [4]: x = empty((2, 2), dt)
In [5]: xa = x[dt.names[0]]
In [6]: xa[:] = [[1,2], [3,4]]
In [7]: xb = x[dt.names[1]]
In [8]: xb[:] = [[1,2], [3,4]]
In [9]: x.sort()
In [11]: x
Out[11]:
array([[(1, 1), (2, 2)],
[(3, 3), (4, 4)]],
dtype=[('aaa', '|u1'), ('bbb', '|u1')])
Chuck
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