On my side both function perform equally. although test2 had to be timed
twice to get to the same performance.
julia> test2(x)= sum( [t^2 for t in x] )
julia> @time test2(r)
0.017423 seconds (13.22 k allocations: 1.339 MB)
julia> @time test2(r)
0.000332 seconds (9 allocations: 781.531 KB)
I think the discrepancy comes from the JITing process because if I time it
without using the macro @time, it works from the first run.
julia> test2(x)= sum( [t^2 for t in x] )
WARNING: Method definition test2(Any) in module Main at REPL[68]:1
overwritten at REPL[71]:1.
test2 (generic function with 1 method)
julia> tic();for i=1:10000 ; test2(r);end;toc()/10000
elapsed time: 3.090764498 seconds
0.0003090764498
About the memory footprint -> test2 first constructs the inner vector then
calls sum.
since the type was not inferred the zero-element could not be created.
>
The sum of an empty set or vector is undefined it is not zero.
you can rewrite it in a more explicit way
test3(r) = begin
total = Float64(0);
for t in r total+=t ;end;end
On Thursday, September 22, 2016 at 10:50:39 PM UTC+3, Patrick Kofod
Mogensen wrote:
>
> I've seen the same, and the answer I got at the JuliaLang gitter channel
> was that it could not be inferred because r could be of length 0, and in
> that case, the return type could not be inferred. My Julia-fu is too weak
> to then explain why the comprehension would be able to infer the return
> type.
>
> On Thursday, September 22, 2016 at 9:27:37 PM UTC+2, Stefan Karpinski
> wrote:
>>
>> I see the same, yet:
>>
>> julia> r = rand(10^5);
>>
>> julia> @time test1(r)
>> 0.000246 seconds (7 allocations: 208 bytes)
>> 33375.54531253989
>>
>> julia> @time test2(r)
>> 0.001029 seconds (7 allocations: 781.500 KB)
>> 33375.54531253966
>>
>>
>> So test1 is efficient, despite the codewarn output. Not sure what's up.
>>
>> On Thu, Sep 22, 2016 at 2:21 PM, Christoph Ortner <christop...@gmail.com>
>> wrote:
>>
>>> I hope that there is something I am missing, or making a mistake in the
>>> following example:
>>>
>>> r = rand(10)
>>> test1(r) = sum( t^2 for t in r )
>>> test2(r)= sum( [t^2 for t in r] )
>>> @code_warntype test1(r) # return type Any is inferred
>>> @code_warntype test2(r) # return type Float64 is inferred
>>>
>>>
>>> This caused a problem for me, beyond execution speed: I used a generator
>>> to create the elements for a comprehension, since the type was not inferred
>>> the zero-element could not be created.
>>>
>>> Is this a known issue?
>>>
>>
>>
