AFAIK deepcopy should never be overloaded. From the docstring: While it isn't normally necessary, user-defined types can override the > default deepcopy behavior by defining a specialized version of the > function deepcopy_internal(x::T, dict::ObjectIdDict) (which shouldn't > otherwise be used), where T is the type to be specialized for, and dict > keeps track of objects copied so far within the recursion. Within the > definition, deepcopy_internal should be used in place of deepcopy, and > the dict variable should be updated as appropriate before returning. >
On Sun, Aug 14, 2016 at 3:03 PM, Tommy Hofmann <[email protected]> wrote: > But for users the following might be surprising: If a user defines > deepcopy(::T) for a user defined type T and x is of type Array{T, 1}, then > deepcopy(x) is not the "same" as [ deepcopy(z) for z in x]. At least this > is my experience and how I understand deepcopy.jl. > > > On Sunday, August 14, 2016 at 8:31:20 PM UTC+2, Cedric St-Jean wrote: >> >> instead, it puts the same object (which is a copy) in the first and third >>> positions and you get the same behavior. Maybe this is not the intended >>> behavior of deepcopy? >>> >> >> It's intentional. deepcopy has to keep and update a dictionary as it >> traverses the datastructure in order to provide the behaviour. Without it, >> it would be impossible to copy cyclic data-structures, as the recursive >> traversal would never end. >> >> On Sunday, August 14, 2016 at 11:36:04 AM UTC-4, Tommy Hofmann wrote: >>> >>> Indeed, the behavior of deepcopy with respect to arrays of user defined >>> types is surprising. >>> >>> If you define >>> >>> Base.deepcopy_internal(x::MyType, ::ObjectIdDict) = >>> MyType(deepcopy(x.a)) >>> >>> then deepcopy(MyType_Vec[[1, 3, 1]]) gives a new object with >>> "independent" elements. See also http://docs.julialang.org >>> /en/release-0.4/stdlib/base/#Base.deepcopy >>> >>> >>> On Friday, August 12, 2016 at 8:56:32 PM UTC+2, Josh Langsfeld wrote: >>>> >>>> For your second question, I would have expected just doing >>>> deepcopy(MyType_Vec[[1,3,1]]) would have created a new array with a >>>> new object allocated for each element. Instead, it puts the same object >>>> (which is a copy) in the first and third positions and you get the same >>>> behavior. Maybe this is not the intended behavior of deepcopy? >>>> >>>> You can easily get around though this by explicitly calling deepcopy on >>>> each element directly: MyType_Vec = map(deepcopy, MyType_Vec[[1,3,1]]). >>>> A similar alternative with an array comprehension would be: MyType_Vec >>>> = [deepcopy(MyType_Vec[i]) for i in [1,3,1]]. >>>> >>>> (an array comprehension also answers your first question: MyType_Vec = >>>> [MyType([0.0]) for i=1:3]) >>>> >>>> On Friday, August 12, 2016 at 11:47:39 AM UTC-4, Jan wrote: >>>> >>>> I have a beginner question for which I cannot find the answer after >>>>> quite some searching. >>>>> >>>>> >>>>> type MyType >>>>> a::Array{Float64,1} >>>>> end >>>>> >>>>> # Fill an array with "independent" instances of MyType. (By the way, >>>>> is there a shorter way to do this?) >>>>> >>>>> MyType_Vec = Array(MyType, 3); >>>>> >>>>> for i in eachindex(MyType_Vec) >>>>> >>>>> MyType_Vec[i] = MyType([0.0]); >>>>> >>>>> end >>>>> >>>>> MyType_Vec >>>>> >>>>> # Change the value of MyType_Vec[1].a[1] to 2. >>>>> >>>>> MyType_Vec[1].a[1] = 2; >>>>> >>>>> MyType_Vec >>>>> >>>>> # Shuffle the vector but with repeated elements >>>>> >>>>> MyType_Vec = MyType_Vec[[1,3,1]]; >>>>> >>>>> # Change the value of MyType_Vec[1].a[1] to 4. >>>>> >>>>> MyType_Vec[1].a[1] = 4; >>>>> >>>>> MyType_Vec >>>>> >>>>> # The value of MyType_Vec[3].a[1] also changed to 4. >>>>> >>>>> >>>>> How can I avoid this reference behaviour? I want that, after the >>>>> shuffling step, the 3 elements of MyType_Vec should be "independent" so >>>>> that if I change MyType_Vec[1].a[1] nothing else is affected. I have >>>>> tried copy and deepcopy without success. >>>>> >>>>> I would be very happy if someone could help me out. I'm stuck... >>>>> >>>>> Many thanks in advance. >>>>> >>>> >>>> >>>
