Hi,
I noticed that I can index into a dtype when I take an element
of a rank-1 array but not if I make a rank-0 array directly. This seems
inconsistent. A bug?
Nils
In [76]: np.version.version
Out[76]: '1.5.1'
In [78]: dt = np.dtype([('x', 'f8'), ('y', 'f8')])
In [80]: a_rank_1 =
On Mon, Jan 10, 2011 at 10:08, Nils Becker n.bec...@amolf.nl wrote:
Hi,
I noticed that I can index into a dtype when I take an element
of a rank-1 array but not if I make a rank-0 array directly. This seems
inconsistent. A bug?
Not a bug. Since there is no axis, you cannot use integers to
Robert,
your answer does work: after indexing with () I can then further index
into the datatype.
In [115]: a_rank_0[()][0]
Out[115]: 0.0
I guess I just found the fact confusing that a_rank_1[0] and a_rank_0
compare and print equal but behave differently under indexing.
More precisely if I do
On Mon, Jan 10, 2011 at 12:15, Nils Becker n.bec...@amolf.nl wrote:
Robert,
your answer does work: after indexing with () I can then further index
into the datatype.
In [115]: a_rank_0[()][0]
Out[115]: 0.0
I guess I just found the fact confusing that a_rank_1[0] and a_rank_0
compare and
