Actually, Int (and UInt) are aliases to the “native size integer”, so if
you specify Int you will get Int32 on a 32-bit system and Int64 on a 64-bit
system. So no, don’t change my_var::Int to my_var::Int32 - that’ll make
your code *worse* on 64-bit systems ;)
// T
On Monday, August 25, 2014 9:05:06 PM UTC+2, Roy Wang wrote:
> Thanks guys. So to clarify: FloatingPoint is not a concrete types, so
> explicitly defining variables or function inputs using it will not speed
> things up. Instead, I should use Float64, Float32, etc.
>
> Is Int an abstract type as well? I'm wondering if I should go back and
> rename everything my_var::Int to my_var::Int32.
>
> John: I couldn't find the mutate!() function in the Julia Standard Library
> v0.3. Do you mean my own function that mutates the source array?
>
> On Monday, 25 August 2014 14:54:14 UTC-4, Patrick O'Leary wrote:
>>
>> On Monday, August 25, 2014 12:28:00 PM UTC-5, John Myles White wrote:
>>>
>>> Array{FloatingPoint} isn't related to Array{Float64}. Julia's type
>>> system always employs invariance for parametric types:
>>> https://en.wikipedia.org/wiki/Covariance_and_contravariance_(computer_science)
>>>
>>> <https://www.google.com/url?q=https%3A%2F%2Fen.wikipedia.org%2Fwiki%2FCovariance_and_contravariance_%28computer_science%29&sa=D&sntz=1&usg=AFQjCNH5Mpuwh71o9dv0_TDx9OcMvvKfWg>
>>>
>>
>> To underline this point a bit, it's even a bit worse than that:
>> Array{FloatingPoint} will work just fine for a lot of things, but it stores
>> all elements as heap pointers, so array-like operations (such as linear
>> algebra routines) will often be extremely slow.
>>
>> As a rule, you almost never use an abstract type as the type parameter of
>> a parametric type for this reason. Where you wish to be generic over a
>> specific family of types under an abstract type, you can use type
>> constraints:
>>
>> function foo{T<:FloatingPoint}(src::Array{T,1})
>> ...
>> end
>>
>> But often type annotations can be omitted completely.
>>
>
