> function testparse()
> parse("4.123456789")
> end
Try:
function testparse()
parse(Float64, "4.123456789")
end
I get 100x speedup.
> @time testparse()
> @time for i=1:10000
> testparse()
> end
> Running this on the same machine takes about 0.65 seconds. I get similar
> results if I call @time for a single call to
> testparse(), and any other variations I could think of. This indicates
> julia's parse is about a factor of 80 slower than the equivalent
> in C++.
>
> Have I done something to make this slow, or is parse just very slow? Why
> would it be so slow?
>
> -Steve
>
>
> On Friday, December 25, 2015 at 2:20:21 AM UTC-8, Adrian Cuthbertson wrote:
>>
>> The essential part first:
>>
>> julia> a,b,c,d=map(parse,split("9 2 2 1.3\n"))
>> 4-element Array{Real,1}:
>> 9
>> 2
>> 2
>> 1.3
>>
>> but see what you actually get back...
>> julia> typeof(a)
>> Int64
>> julia> typeof(d)
>> Float64
>>
>> That's Julia's type inferencing at play. And functional abilities (map,
>> parse). See the manual on those.
>>
>> Now as originally needed...
>>
>> julia> io=IOBuffer("9 2 2 1.3\n")
>> IOBuffer(data=UInt8[...], readable=true, writable=false, seekable=true,
>> append=false, size=10, maxsize=Inf, ptr=1, mark=-1)
>>
>> julia> n,nup,ndn,a=map(parse,split(readline(io)))
>> 4-element Array{Real,1}:
>> 9
>> 2
>> 2
>> 1.3
>>
>> julia> typeof(n)
>> Int64
>>
>> julia> typeof(a)
>> Float64
>>
>> It's probably better to do it properly in a function rather than like that
>> as a one-liner - so you can catch exceptions, etc.
>>
>> -- Adrian.
>>
>>
>> On Thu, Dec 24, 2015 at 8:36 PM, Steven White <[email protected]
>> <javascript:>> wrote:
>>
>>> Say I have a data file in plain text, which starts with some lines that
>>> describe matrix sizes, etc, for the data that follows. For example, the
>>> first line might be
>>> 9 2 2 1.3
>>>
>>> To read this file, in C I would use something like this call to scanf:
>>> scanf("%d%d%d%lf",&n,&nup,&ndn,&a);
>>>
>>> How do I do this in julia? There doesn't seem to be a simple, obvious
>>> way. Of course, you can read the line as a string, and parse it using
>>> regular expressions, but this is much messier than the call to scanf.
>>>
>>> Here is a solution:
>>> getline() = readdlm(IOBuffer(readline()),Any)
>>>
>>> n,nup,ndn,a = getline()
>>>
>>> This seems to work reliably. (For example, it doesn't choke if there
>>> happen to be two spaces between some of the numbers.)
>>>
>>> It is also obscure and doesn't give any warnings if some of the types
>>> aren't what was expected. It also seems inefficient if you try to read a
>>> lot of data this way.
>>>
>>> Questions: Why isn't something like this (but better) built in to
>>> julia? Is there some nice method that I've missed that does this better?
>>> Can this getline() function be improved?
>>>
>>>
>>
