There is no plans for namespace support other than what's already in with
modules.
I'll try to explain. Say you have a mutable
type foo
a::Int
b::Int
end
Then to modify it in a function you have to explicitly say
function bar(f::foo)
f.a = 2
f.b = 3
end
etc., for it to modify my argument foo. I think it's way too easy to
refactor a function say
function bar(f::foo)
... lots of stuff ...
a = 2*f.a
... lots of stuff ...
f.b*10*a
end
into
function bar(f::foo)
using f
... lots of stuff ...
a = 2*f.a
... lots of stuff ...
b*10*a
end
because you want to immediately access b, but forgot that foo also has an a
field. In general in julia an assignment like
var = value
will almost never have effects outside it's current scope (var[idx] = and
var.field = are different). The only exception to this is if you write
function test()
global var
var = value
end
but as you can see that annotation is very explicit and limited. I would be
similarly opposed to a language feature that causes all variables in a
function to implicitly be global.
As I said this isn't a concern in the immutable case because the subsequent
assignment would always override the original value and simple assignments
will not have effects outside the current scope. This can be implemented
with macros though.
Hope that clarifies it,
Keno
On Thu, Jun 12, 2014 at 1:30 AM, Andrew Simper <[email protected]>
wrote:
> Are namespaces going to be supported in julia? It would be the same
> mechanism as that, an order of preference to choose what a particular name
> is referring to, no more. So if julia is not going to support "using" on a
> namespace then I completely understand not wanting to support it on
> variables as I have suggested.
>
> I don't follow what you mean by "The mutable case has me worried. It
> introduces the possibility that an assingment (a simple one, not a setfield
> or getindex) actually has effects outside of the function which doesn't
> happen anywhere else in julia."
>
> Can you please provide an example to illustrate what you are worried about?
>
>
> On Thursday, June 12, 2014 1:21:14 PM UTC+8, Keno Fischer wrote:
>
>> In my opinion, looking at that example this is way to magical. Plus the
>> general consensus is that you should only add syntax if it is something
>> extremely special that requires compiler support. For the non-mutable case,
>> that's not the case here. The mutable case has me worried. It introduces
>> the possibility that an assingment (a simple one, not a setfield or
>> getindex) actually has effects outside of the function which doesn't happen
>> anywhere else in julia.
>>
>>
>> On Thu, Jun 12, 2014 at 1:07 AM, Andrew Simper <[email protected]>
>> wrote:
>>
>>> The problem with using a macro is that you will always have to make a
>>> local copy of the data, if it was a language feature then then a mutable
>>> type could be passed in as the argument and the same non-obfuscated code
>>> could be used to update the state in place, which may be preferable
>>> depending on the situation.
>>>
>>> Here is another example from the Julia.org webpage:
>>>
>>> immutable Pixel
>>> r::Uint8
>>> g::Uint8
>>> b::Uint8
>>> end
>>>
>>> function rgb2gray!(img::Array{Pixel})
>>> for i=1:length(img)
>>> p = img[i]
>>> v = uint8(0.30*p.r + 0.59*p.g + 0.11*p.b)
>>> img[i] = Pixel(v,v,v)
>>> end
>>> end
>>>
>>> function rgb2gray2!(img::Array{Pixel})
>>> for i=1:length(img)
>>> using img[i]
>>> v = uint8(0.30*r + 0.59*g + 0.11*b)
>>> img[i] = Pixel(v,v,v)
>>> end
>>> end
>>>
>>>
>>>
>>> On Thursday, June 12, 2014 12:30:05 PM UTC+8, Keno Fischer wrote:
>>>
>>>> I don't think it warrants syntax, but might be nice in a macro. I've
>>>> had cases where I just put my entire simulation state in a single object,
>>>> so I don't need to give 100s of parameters to every object. In that case
>>>> (where the object is more of a container than an abstraction), it might be
>>>> nice to use.
>>>>
>>>>
>>>> On Thu, Jun 12, 2014 at 12:13 AM, Andrew Simper <[email protected]>
>>>> wrote:
>>>>
>>>>> So just to post again to make things clearer, right now algorithms
>>>>> tend to look pretty ugly and obfuscated since you have to prefix function
>>>>> arguments with the argument names using dot notation:
>>>>>
>>>>> function tick (state::SvfSinOsc, coef::SvfSinOscCoef)
>>>>> local v1::Float64 = coef.g0*state.ic1eq - coef.g1*state.ic2eq
>>>>> local v2::Float64 = coef.g1*state.ic1eq + coef.g0*state.ic2eq
>>>>> SvfSinOsc (2*v1 - state.ic1eq, 2*v2 - state.ic2eq)
>>>>> end
>>>>>
>>>>>
>>>>> This is a lot more readable to me, and it would be super useful to
>>>>> have a "using" type operation similar to namespace but it could run on
>>>>> variables instead, so that although writing the following is equivalent to
>>>>> what is above, it is much easier to see what is going on:
>>>>>
>>>>> function tick (state::SvfSinOsc, coef::SvfSinOscCoef)
>>>>> using state, coef
>>>>> local v1::Float64 = g0*ic1eq - g1*ic2eq
>>>>> local v2::Float64 = g1*ic1eq + g0*ic2eq
>>>>> SvfSinOsc (2*v1 - ic1eq, 2*v2 - ic2eq)
>>>>> end
>>>>>
>>>>> What are peoples opinions on this? Would anyone else find it useful?
>>>>>
>>>>>
>>>>>
>>>>> On Friday, June 6, 2014 3:17:31 PM UTC+8, Andrew Simper wrote:
>>>>>>
>>>>>> In implementations where you want named data, I've noticed that the
>>>>>> algorithm gets obfuscated by lots of variable names with dots after them.
>>>>>> For example, here is a basic analog model of a state variable filter used
>>>>>> as a sine wave generator:
>>>>>>
>>>>>> immutable SvfSinOscCoef
>>>>>> g0::Float64
>>>>>> g1::Float64
>>>>>> end
>>>>>> immutable SvfSinOsc
>>>>>> ic1eq::Float64
>>>>>> ic2eq::Float64
>>>>>> end
>>>>>> function SvfSinOscCoef_Init (;freq=1.0, sr=44100.0)
>>>>>> local g::Float64 = tan (2pi*freq/sr)
>>>>>> local g0 = 1.0/(1.0+g^2)
>>>>>> SvfSinOscCoef (g0,g*g0)
>>>>>> end
>>>>>> function SvfSinOsc_Init (startphase::Float64)
>>>>>> SvfSinOsc (cos(startphase), sin(startphase))
>>>>>> end
>>>>>>
>>>>>> But the tick function looks a bit messy:
>>>>>>
>>>>>> function tick (state::SvfSinOsc, coef::SvfSinOscCoef)
>>>>>> local v1::Float64 = coef.g0*state.ic1eq - coef.g1*state.ic2eq
>>>>>> local v2::Float64 = coef.g1*state.ic1eq + coef.g0*state.ic2eq
>>>>>> SvfSinOsc (2*v1 - state.ic1eq, 2*v2 - state.ic2eq)
>>>>>> end
>>>>>>
>>>>>>
>>>>>> It would be really cool if there was a way to shorthand the syntax of
>>>>>> this to something like the following, which is a lot more readable:
>>>>>>
>>>>>> function tick (state::SvfSinOsc, coef::SvfSinOscCoef)
>>>>>> using s, c
>>>>>> local v1::Float64 = g0*ic1eq - g1*ic2eq
>>>>>> local v2::Float64 = g1*ic1eq + g0*ic2eq
>>>>>> SvfSinOsc (2*v1 - ic1eq, 2*v2 - ic2eq)
>>>>>> end
>>>>>>
>>>>>>
>>>>>> Lots of algorithms have arguments with the same type, but even then
>>>>>> you could still specify using just the most used argument, but if it
>>>>>> doesn't help make things more clear or isn't useful then people don't
>>>>>> have
>>>>>> to use it at all.
>>>>>>
>>>>>>
>>>>>>
>>>>>> Another pattern that would be nice to handle cleanly is: fetch state
>>>>>> to local, compute on local, store local to state. I have written code
>>>>>> that
>>>>>> generates code to handle this since it is such a pain to keep everything
>>>>>> in
>>>>>> sync, but if there was some way to automate this at the language level
>>>>>> then
>>>>>> it would really rock, so here is an example of the longhand way, which
>>>>>> isn't too bad for this example, but just imagine if there are 20 or so
>>>>>> variables, and you are writing multiple tick functions:
>>>>>>
>>>>>> type SvfSinOsc
>>>>>> ic1eq::Float64
>>>>>> ic2eq::Float64
>>>>>> end
>>>>>>
>>>>>> function tick (state::SvfSinOsc, coef::SvfSinOscCoef)
>>>>>> local ic1eq::Float64 = state.ic1eq
>>>>>> local ic2eq::Float64 = state.ic2eq
>>>>>> for i = 1:100
>>>>>> # compute algorithm using local copies of state.ic1eq and
>>>>>> state.ic2eq
>>>>>> end
>>>>>> state.ic1eq = ic1eq
>>>>>> state.ic2eq = ic2eq
>>>>>> return state
>>>>>> end
>>>>>>
>>>>>>
>>>>>> I have a feeling that macros may be able to help out here to result
>>>>>> in something like:
>>>>>>
>>>>>> function tick (state::SvfSinOsc, coef::SvfSinOscCoef)
>>>>>> @fetch state
>>>>>> for i = 1:100
>>>>>> # compute iterative algorithm using local copies of
>>>>>> state.ic1eq and state.ic2eq
>>>>>> end
>>>>>> @store state
>>>>>> return state
>>>>>> end
>>>>>>
>>>>>> But I'm not sure how to code such a beast, I tried something like:
>>>>>>
>>>>>> macro fetch(obj::SvfSinOsc)
>>>>>> return quote
>>>>>> local ic1eq = obj.ic1eq
>>>>>> local ic2eq = obj.ic2eq
>>>>>> end
>>>>>> end
>>>>>>
>>>>>> macro store(obj::SvfSinOsc)
>>>>>> return quote
>>>>>> obj.ic1eq = ic1eq
>>>>>> obj.ic2eq = ic2eq
>>>>>> end
>>>>>> end
>>>>>>
>>>>>> dump(osc)
>>>>>> macroexpand (:(@fetch osc))
>>>>>> macroexpand (:(@store osc))
>>>>>>
>>>>>>
>>>>>> SvfSinOsc
>>>>>> ic1eq: Float64 1.0
>>>>>> ic2eq: Float64 0.0
>>>>>>
>>>>>>
>>>>>> Out[28]: :($(Expr(:error, TypeError(:anonymous,"typeasse
>>>>>> rt",SvfSinOsc,:osc))))
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>>>
>>>>
>>
