[Numpy-discussion] Interesting timing results

[Travis Oliphant]

Sasha wrote:

>>python -m timeit -s "x=bool(0)" "x or x"
>>    
>>
>10000000 loops, best of 3: 0.111 usec per loop
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>>python -m timeit -s "from numpy import bool_, logical_or as or_; x=bool_(0)" "or_(x, x)"
>>    
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>100000 loops, best of 3: 3.25 usec per loop
>
>Numpy is 32x slower than python -- not very good.
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This is a known fact.  Currently all array scalar math goes through the 
entire ufunc machinery.  This is clearly sub-optimal.   It is the reason 
for the scalarmath module that I've started in the src directory.   
Eventually, we should be able to have scalar math as fast as Python 
scalars.

Anybody wanting to help out.  This is a good place.  One issue is how to 
handle scalar math division-by-zero, and overflow errors.  Ideally these 
should be handled the same way that ufuncs do.  But, this will 
necessarily cause some slow-down to look up the local and-or 
module-level attribute that can alter the behavior. 

-Travis

>Interestingly,
>
>  
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>>python -m timeit -s "from numpy import bool_; x=bool_(0)" "x or x"
>>    
>>
>1000000 loops, best of 3: 0.388 usec per loop
>  
>

Again, not too surprising given that logical_or goes through the ufunc 
machinery...

-Travis