Re: [Numpy-discussion] optimizing power() for complex and real cases

[Travis O. <oli...@ie...>]

Tim Hochberg wrote:

> Yeah, sort of. I meant that the little helper functions that ufuncs 
> call, such as DOUBLE_multiply,  take the same types of arguments. 
> However, I just realized that I'm not certain that's true -- I just 
> assumed it because all the one's I've ever seen do. Also, this isn't 
> really a problem anyway -- the real problem is the slow conversion of 
> Python scalars to arrays in ufuncs.

Yes, that is true.  We have only defined multiplication for same-types.  
But, I just wanted to clarify that the ufunc machinery is more general 
than that, because others have been confused in the past. 

> I took a look at this earlier and it appears that the reason that 
> conversion of Python scalars are slow is that FromAny trys every other 
> conversion first. The check for Python scalars looks pretty cheap, so 
> it seems reasonable to check for them and do the appropriate 
> conversion early. Do the ufunc's call EnsureArray or FromAny? If the 
> former it would seem pretty straighforward to just stick another check 
> in there. Then David's original strategy of optimizing in DOUBLE_pow 
> should be close to as fast as what I'm doing.

Yes, I suspect the biggest slow-downs are the two attribute lookups 
which allow anything with __array__ or the array interface defined to be 
used. 

I think we could special-case Python scalars in that code.

-Travis