Is adding arbitrary optional parameters a thing with ufuncs? I could easily
add upper and lower bounds checks.

On Thu, Dec 30, 2021, 20:56 Brock Mendel <jbrockmen...@gmail.com> wrote:

> At least some of the commenters on that StackOverflow page need a slightly
> stronger check: not only is_integer(x), but also "np.iinfo(dtype).min <= x
> <= np.info(dtype).max" for some particular dtype.  i.e. "Can I losslessly
> set these values into the array I already have?"
>
>
>
> On Thu, Dec 30, 2021 at 4:34 PM Joseph Fox-Rabinovitz <
> jfoxrabinov...@gmail.com> wrote:
>
>> Hi,
>>
>> I wrote a reference implementation for a C ufunc, `isint`, which returns
>> True for integers and False for non-integers, found here:
>> https://github.com/madphysicist/isint_ufunc. The idea came from a Stack
>> Overflow question of mine, which has gotten a fair number of views and even
>> some upvotes: https://stackoverflow.com/q/35042128/2988730. The current
>> "recommended" solution is to use ``((x % 1) == 0)``. This is slower and
>> more cumbersome because of the math operations and the temporary storage.
>> My version returns a single array of booleans with no intermediaries, and
>> is between 5 and 40 times faster, depending on the type and size of the
>> input.
>>
>> If you are interested in taking a look, there is a suite of tests and a
>> small benchmarking script that compares the ufunc against the modulo
>> expression. The entire thing currently works with bit twiddling on an
>> appropriately converted integer representation of the number. It assumes a
>> standard IEEE754 representation for float16, float32, float64. The extended
>> 80-bit float128 format gets some special treatment because of the explicit
>> integer bit. Complex numbers are currently integers only if they are real
>> and integral. Integer types (including bool) are always integers. Time and
>> text raise TypeErrors, since their integerness is meaningless.
>>
>> If a consensus forms that this is something appropriate for numpy, I will
>> need some pointers on how to package up C code properly. This was an
>> opportunity for me to learn to write a basic ufunc. I am still a bit
>> confused about where code like this would go, and how to harness numpy's
>> code generation. I put comments in my .c and .h file showing how I would
>> expect the generators to look, but I'm not sure where to plug something
>> like that into numpy. It would also be nice to test on architectures that
>> have something other than a 80-bit extended long double instead of a proper
>> float128 quad-precision number.
>>
>> Please let me know your thoughts.
>>
>> Regards,
>>
>> - Joe
>> _______________________________________________
>> NumPy-Discussion mailing list -- numpy-discussion@python.org
>> To unsubscribe send an email to numpy-discussion-le...@python.org
>> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
>> Member address: jbrockmen...@gmail.com
>>
> _______________________________________________
> NumPy-Discussion mailing list -- numpy-discussion@python.org
> To unsubscribe send an email to numpy-discussion-le...@python.org
> https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
> Member address: jfoxrabinov...@gmail.com
>
_______________________________________________
NumPy-Discussion mailing list -- numpy-discussion@python.org
To unsubscribe send an email to numpy-discussion-le...@python.org
https://mail.python.org/mailman3/lists/numpy-discussion.python.org/
Member address: arch...@mail-archive.com

Reply via email to