El sábado, 31 de enero de 2015, 15:46:50 (UTC+3), David P. Sanders escribió:
>
>
>
> El sábado, 31 de enero de 2015, 15:35:49 (UTC+3), Jiahao Chen escribió:
>>
>> Hm, this is a tough one. The imaginary unit im is currently defined to be
>> of type Complex{Bool}, which seems to be the cause of the type instability.
>> Previously im was its own ImaginaryUnit type, which meant that very few
>> functions were defined on just im and also led to a lot of unwanted NaNs
>> cropping up in computations.
>>
>
> What is the reason why `im` is not just defined as `Complex(0,1)`?
>
Oh, I guess there's the obvious issue of what type the real and imaginary
parts should be.
So really, im should be parametrised on this type.
> I'm sure there's a good one, since this must have been thought about at
> length, but I'd like to know what it is or have a reference to the
> discussion.\
>
> Best,
> David.
>
>
>
>> Thanks,
>>
>> Jiahao Chen
>> Staff Research Scientist
>> MIT Computer Science and Artificial Intelligence Laboratory
>>
>> On Sat, Jan 31, 2015 at 5:53 AM, Tim Holy <[email protected]> wrote:
>>
>>> There seem to be some problems with type inference and `im`. If at the
>>> beginning of the function I define
>>> myim = convert(Complex128, im)
>>> and then replace all uses of `im` with `myim`, then everything works as
>>> expected.
>>>
>>> Can you file an issue, please?
>>>
>>> --Tim
>>>
>>> On Friday, January 30, 2015 09:48:26 PM Kirill Ignatiev wrote:
>>> > I have a newbie-type performance question.
>>> >
>>> > In some of my code there is a structure that looks like this:
>>> >
>>> > type FourierPoly
>>> >
>>> > > periods :: Vector{Int}
>>> > > radiuses :: Vector{Float64}
>>> > > phase_offsets :: Vector{Float64}
>>> > >
>>> > > end
>>> >
>>> > and the following two functions that operate on it:
>>> >
>>> > - function polyval(f::FourierPoly, t::Float64)
>>> >
>>> > > 33694968 s = zero(Complex128)
>>> > >
>>> > > 0 @inbounds for k = 1:length(f.periods)
>>> > > 0 s += exp(2.pi*(t + f.phase_offsets[k]) * f.periods[k]
>>> * im)
>>> > >
>>> > > * f.radiuses[k]
>>> > >
>>> > > - end
>>> > > 0 return s::Complex128
>>> > > 0 end
>>> > > 0
>>> > > 0 function polyder(f::FourierPoly, t::Float64)
>>> > > 0 s = zero(Complex128)
>>> > >
>>> > > 492303248 @inbounds for k = 1:length(f.periods)
>>> > >
>>> > > 0 θ = 2.pi * f.periods[k]
>>> > >
>>> > > 164100720 s += θ * im * exp((t + f.phase_offsets[k]) * θ * im) *
>>> > > f.radiuses[k]
>>> > >
>>> > > 257652 end
>>> > >
>>> > > 0 return s::Complex128
>>> > > - end
>>> >
>>> > (copied from output of julia run with --track-allocation=user).
>>> >
>>> > What is the difference between these two functions? polyval seems
>>> fine, but
>>> > polyder is called at most as often as polyval from the rest of the
>>> code,
>>> > yet its memory consumption is at least an order of magnitude higher?
>>> Can
>>> > somebody please point out what I'm missing here?
>>>
>>>
>>
