This surprised me as well, where did you find this syntax?
On Monday, September 12, 2016 at 1:59:33 PM UTC+2, DNF wrote:
>
> I haven't looked very closely at your code, but a brief look reveals that
> you are defining your functions in a very unusual way. Two examples:
>
> function (f::FIRFilter)(x)
> return filt(f, x)
> end
>
> function(p::pnseq)(n,T=Int64)
> out = Array{T}(n)
> for i in eachindex(out)
> if p.count < p.width
> p.cache = rand(Int64)
> p.count = 64
> end
> out[i] = p.cache & p.mask
> p.cache >>= p.width
> p.count -= p.width
> end
> return out
> end
>
> I have never seen this way of defining them before, and I am pretty
> surprised that it's not a syntax error. Long-form function signatures
> should be of the form
> function myfunc{T<:SomeType}(myarg1::T, myarg2)
> where the type parameter section (in curly bracket) is optional.
>
> As I said, I'm surprised it's not a syntax error, but maybe it gets parsed
> as an anonymous function (just guessing here). If so, and if you are using
> version 0.4, you can get slow performance.
>
> You can read here about the right way to define functions:
> http://docs.julialang.org/en/stable/manual/functions/
>
> On Monday, September 12, 2016 at 1:32:48 PM UTC+2, Neal Becker wrote:
>>
>> As a first (nontrivial) try at julia, I put together some simple DSP
>> code,
>> which represents a
>> pn generator (random fixed-width integer generator)
>> constellation mapping
>> interpolating FIR filter (from DSP.jl)
>> decimating FIR filter (from DSP.jl)
>> mean-square error measure
>>
>> Source code is here:
>> https://github.com/nbecker/julia-test
>>
>> Profile result is here:
>> https://gist.github.com/anonymous/af2459fc831ddbeb6e3be25e5c8d5197
>>
>> If I understand how to read this profile (not sure I do) it looks like
>> 1/2
>> the time is spent in PnSeq.jl, which seems surprising.
>>
>> PnSeq.jl calls rand() to get a Int64, caching the result and then
>> providing
>> N bits at a time to fill an Array. It's supposed to be a fast way to get
>> an
>> Array of small-width random integers.
>>
>> Most of the number crunching should be in the FIR filter functions, which
>> I
>> would have expected to use the most time.
>>
>> Anyone care to make suggestions on this code, how to make it faster, or
>> more
>> idiomatic Julia? I'm not proficient with Julia or with Matlab (I've been
>> using python/numpy/c++ for all my work for years).
>>
>>
>>
