I'm going to guess either it's because of the anonymous function definition
within your map function. Note that you aren't getting *exactly* the same
results, as the Array types are different.
It also isn't universally true that comprehensions are faster. See the
following counter-example:
*julia> **s = ["as", "sdf", "qwer"]*
*3-element Array{ASCIIString,1}:*
* "as" *
* "sdf" *
* "qwer"*
*julia> **@time [length(i) for i in s]*
0.000019 seconds (10 allocations: 384 bytes)
*3-element Array{Any,1}:*
* 2*
* 3*
* 4*
*julia> **@time map(length, s)*
0.000015 seconds (5 allocations: 256 bytes)
*3-element Array{Int64,1}:*
* 2*
* 3*
* 4*
In this case (after multiple runs), map is even or just slightly faster
than a comprehension. I presume map is faster here because it knows the
result of function will be Array{Int64}, where as the comprehension Julia
doesn't know and returns an Array{Any}
On Wednesday, October 21, 2015 at 8:55:50 AM UTC-4, Ján Dolinský wrote:
>
> Hi,
>
> I'd like to check which approach is a better one for the example below.
> The task is rather simple, each string in vector "s" should be "surrounded"
> by square brackets.
>
> e.g.
>
> s = AbstractString["as", "sdf", "qwer"] # s is typically a lot longer
>
> @time st1 = AbstractString[ "[" * i * "]" for i in s ]
> 0.000057 seconds (16 allocations: 672 bytes)
> 3-element Array{AbstractString,1}:
> "[as]"
> "[sdf]"
> "[qwer]"
>
> @time st2 = map(x->"["*x*"]", s)
> 0.002932 seconds (33 allocations: 2.035 KB)
> 3-element Array{ASCIIString,1}:
> "[as]"
> "[sdf]"
> "[qwer]"
>
>
>
> The both expressions yield same results. I wonder whether from the
> language design point of view one approach should be preferred over the
> other. Comprehension here is considerably faster, I wonder why.
>
> Thanks,
> Jan
>
>
