NumPy has the handy np.vectorize for turning Python code that operates on
scalars into a function that vectorizes works like a ufunc, but no helper
function for creating generalized ufuncs (
http://docs.scipy.org/doc/numpy/reference/c-api.generalized-ufuncs.html).
np.apply_along_axis accomplishes
We had a big long discussion about this on this list a while back (maybe 2
yrs ago???) please search the archives to find it. Though I'm pretty sure
that we never did come to a conclusion. I think it stared with wanting
better support ofr unicode in loadtxt and the like, and ended up delving
into
On Tue, Sep 13, 2016 at 11:47 AM, Stephan Hoyer wrote:
> NumPy has the handy np.vectorize for turning Python code that operates on
> scalars into a function that vectorizes works like a ufunc, but no helper
> function for creating generalized ufuncs (http://docs.scipy.org/doc/
On Tue, Sep 13, 2016 at 11:05 AM, Lluís Vilanova
wrote:
> Whenever we repr an array using 'S', we can instead show a unicode in py3.
> That
> keeps the binary representation, but will always show the expected result
> to
> users, and it's only a handful of lines added to
On Tue, Sep 13, 2016 at 10:39 AM, Nathan Goldbaum
wrote:
> I'm curious whether you have a plan to deal with the python functional
> call overhead. Numba gets around this by JIT-compiling python functions -
> is there something analogous you can do in NumPy or will this
Chris Barker writes:
> We had a big long discussion about this on this list a while back (maybe 2 yrs
> ago???) please search the archives to find it. Though I'm pretty sure that we
> never did come to a conclusion. I think it stared with wanting better support
> ofr unicode in loadtxt and the
On Tue, Sep 13, 2016 at 11:05 AM, Lluís Vilanova
wrote:
> Great, that's the type of info I wanted to get before going forward. I
> guess
> there's code relying on the binary representation of 'S' to do mmap's or
> access
> the array's raw contents. Is that right?
yes,
There has been some discussion on the Numba mailing list as well about a
version of guvectorize that doesn't compile for testing and flexibility.
Having this be inside NumPy itself seems ideal.
-Travis
On Tue, Sep 13, 2016 at 12:59 PM, Stephan Hoyer wrote:
> On Tue, Sep 13,
Sebastian Berg writes:
> On Di, 2016-09-13 at 15:02 +0200, Lluís Vilanova wrote:
>> Hi! I'm giving a shot to issue #3184 [1], based on the observation
>> that the
>> string dtype ('S') under python 3 uses byte arrays instead of unicode
>> (the only
>> readable string type in python 3).
>>
>>
Sebastian Berg writes:
> On Di, 2016-09-13 at 15:02 +0200, Lluís Vilanova wrote:
>> Hi! I'm giving a shot to issue #3184 [1], based on the observation
>> that the
>> string dtype ('S') under python 3 uses byte arrays instead of unicode
>> (the only
>> readable string type in python 3).
>>
>>
On Di, 2016-09-13 at 15:02 +0200, Lluís Vilanova wrote:
> Hi! I'm giving a shot to issue #3184 [1], based on the observation
> that the
> string dtype ('S') under python 3 uses byte arrays instead of unicode
> (the only
> readable string type in python 3).
>
> This brings two major problems:
>
>
Hi! I'm giving a shot to issue #3184 [1], based on the observation that the
string dtype ('S') under python 3 uses byte arrays instead of unicode (the only
readable string type in python 3).
This brings two major problems:
* numpy code has to go through loops to open and read files as binary
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