On Tue, Dec 30, 2014 at 11:03 PM, Valentin Haenel <valen...@haenel.co> wrote:
> * Eric Moore <e...@redtetrahedron.org> [2014-12-30]:
>> On Monday, December 29, 2014, Valentin Haenel <valen...@haenel.co> wrote:
>>
>> > Hi,
>> >
>> > how do I access the kind of the data from cython, i.e. the single
>> > character string:
>> >
>> > 'b' boolean
>> > 'i' (signed) integer
>> > 'u' unsigned integer
>> > 'f' floating-point
>> > 'c' complex-floating point
>> > 'O' (Python) objects
>> > 'S', 'a' (byte-)string
>> > 'U' Unicode
>> > 'V' raw data (void)
>> >
>> > In regular Python I can do:
>> >
>> > In [7]: d = np.dtype('S')
>> >
>> > In [8]: d.kind
>> > Out[8]: 'S'
>> >
>> > Looking at the definition of dtype that comes with cython, I see:
>> >
>> > ctypedef class numpy.dtype [object PyArray_Descr]:
>> > # Use PyDataType_* macros when possible, however there are no macros
>> > # for accessing some of the fields, so some are defined. Please
>> > # ask on cython-dev if you need more.
>> > cdef int type_num
>> > cdef int itemsize "elsize"
>> > cdef char byteorder
>> > cdef object fields
>> > cdef tuple names
>> >
>> > I.e. no kind.
The problem is just that whoever wrote numpy.pxd was feeling a bit
lazy that day and only filled in the fields they felt were most
important :-). There are a bunch of public fields in PyArray_Descr
that are just being left out of the Cython file you quote:
https://github.com/numpy/numpy/blob/master/numpy/core/include/numpy/ndarraytypes.h#L566
In particular, there's a 'char kind' field.
The quick workaround is
cdef extern from "*":
cdef struct my_numpy_dtype [object PyArray_Descr]:
cdef char kind
# ... whatever other fields you might need
and then cast to my_numpy_dtype when you need to get at the kind field
from Cython.
If feeling generous, then submit a PR to Cython adding 'cdef char
kind' to the definition above. If feeling extra generous, it would be
awesome if someone systematically went through and added all the
missing fields that are in the numpy header but not cython -- I've run
into these missing field issues annoyingly often myself, and it's
silly that we should all keep making our own individual workarounds
for numpy.pxd's limitations...
-n
--
Nathaniel J. Smith
Postdoctoral researcher - Informatics - University of Edinburgh
http://vorpus.org
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion
