[Numpy-discussion] field names on numpy arrays

[josef.pktd at gmail.com]

2009/6/3 Stéfan van der Walt <stefan at sun.ac.za>:
> Hi Jon
>
> 2009/6/3 D2Hitman <j.m.girven at warwick.ac.uk>:
>> I understand record arrays such as:
>> a_array =
>> np.array([(0.,1.,2.,3.,4.),(1.,2.,3.,4.,5.)],dtype=[('a','f'),('b','f'),('c','f'),('d','f'),('e','f')])
>> do this with field names.
>> a_array['a'] = array([ 0.,  1.], dtype=float32)
>> however i seem to lose simple operations such as multiplication (a_array*2)
>> or powers (a_array**2).
>
> As a workaround, you can have two views on your data:
>
> n [39]: x
> Out[39]:
> array([(0.0, 1.0, 2.0, 3.0, 4.0), (1.0, 2.0, 3.0, 4.0, 5.0)],
>      dtype=[('a', '<f4'), ('b', '<f4'), ('c', '<f4'), ('d', '<f4'),
> ('e', '<f4')])
>
> In [40]: x = x_dict.view(np.float32)
>
> In [41]: x**2
> Out[41]: array([  0.,   1.,   4.,   9.,  16.,   1.,   4.,   9.,  16.,
> 25.], dtype=float32)
>
> Then you can manipulate the same data using two different "interfaces".

Why does it not preserve "shape", to do e.g. np.mean by axis?

>
> Regards
> Stéfan