Only abstract types can be subtyped (and if I recall correctly this is going to stay that way for some type-theory-reason).
Further, at the moment abstract types cannot have fields, i.e. cannot be composite types. However, this might change sometime, have a look at the issue: https://github.com/JuliaLang/julia/issues/4935 (which is also referenced in the mailing list thread mentioned by tshort) Now, all of this does not help with your quest, sorry, but it may be of some interest. On Thu, 2014-01-02 at 16:23, Christian Groll wrote: > My interest lies in the implementation of types that are special cases of > already existing composite types. > > For example, I want to implement a type Portfolio, which is just a > DataFrame with two additional requirements: > - all columns are of numeric type > - the sum of the entries in each row must be equal to 1 > > Or, I want to implement a type TimeSeries, which is just a DataFrame where > the first column consists of dates. > > I think the way to go here would be to implement some type of constraint > checking in the setindex! methods, although this would not prevent messing > with the entries by way of directly setting the fields of the type. > However, once there exist convenient getindex and setindex! methods, I hope > that basically nobody would mess with the values directly, and complete > immutability is not necessarily needed. > > What I am trying to achieve is something that I think is called inheritance > in other languages, where classes can simply be declared as subclasses to > already existing classes. > > So the question is, whether something like this is possible in julia as > well? As far as I get it, there is no way to declare a type to be a subtype > of a composite type. > Or, if this is not possible, is there any way around, like for example > declaring a type portfolio, > > type Portfolio > weights::DataVector{Float64} > end > > where I can simply relate all setindex! methods to the respective methods > of DataVector, adding constraint checks where necessary. > > function Base.setindex!(pf::Portfolio, > v::Any, > col_ind::ColumnIndex) > if check_constraints(pf, v, col_ind) > setindex!(pf.weights, v, col_ind) > else > error("constraints not fulfilled.") > end > end > > However, I then would need some type of metaprogramming such that I do not > have to implement all the numerous setindex! methods of DataVector from > scratch up.
