Nvm, I forgot to export bar from the outer module; doing that, using works
just as well as import, and you don't need to fully qualify (exported)
names in the outer module, just as usual.
// T
On Tuesday, January 6, 2015 1:31:12 AM UTC+1, Tomas Lycken wrote:
>
> The following works for me:
>
> module RCall
>
> module R
>
> import ..RCall
>
> export foo
>
> function foo()
> RCall.bar()
> end
>
> end # R
>
> export R
>
> function bar()
> println("hello, handsome!")
> end
>
> end
>
> Now, I can do
>
> using RCall
> R.foo()
> "hello, handsome!"
>
> I didn’t manage to get it working with using instead of import in the
> inner module, though, but that only affects your own usage of your own
> code, so I think that’s a minor issue.
>
> // T
>
> On Monday, January 5, 2015 10:50:04 PM UTC+1, Douglas Bates wrote:
>
> The (unregistered) [RCall](https://github.com/JuliaStats/RCall.jl)
>> package is an initial cut at the interface. I am not happy with all the
>> names that I chose and welcome suggestions of improvements. For some
>> reason I was unable to create an R module within the RCall module, as
>> Stefan suggested. Again, I welcome suggestions of how to accomplish this.
>> My particular difficulty is that if I create an R module within the RCall
>> module I don't see the names from RCall.
>>
>>
>> On Saturday, January 3, 2015 12:56:48 PM UTC-6, lgautier wrote:
>>>
>>> I agree.
>>> RCall does provide consistency, although at the possible slight cost of
>>> boring conformity, and seems a better choice than RStats.
>>>
>>> On Saturday, January 3, 2015 8:31:42 AM UTC-5, Viral Shah wrote:
>>>>
>>>> I prefer Rcall.jl, for consistency with ccall, PyCall, JavaCall, etc.
>>>> Also, once in JuliaStats, it will probably also be well advertised and
>>>> documented - so finding it should not be a challenge, IMO.
>>>>
>>>> -viral
>>>>
>>>> On Saturday, January 3, 2015 10:16:51 AM UTC+5:30, Ismael VC wrote:
>>>>>
>>>>> +1 for RStats.jl, I also think it's more search-friendly but not only
>>>>> for people coming from R.
>>>>>
>>>>> On Fri, Jan 2, 2015 at 9:50 PM, Gray Calhoun <[email protected]>
>>>>> wrote:
>>>>>
>>>>>> That sounds great! Rcall.jl or RCall.jl are fine names; RStats.jl may
>>>>>> be slightly more search-friendly for people coming from R, since they
>>>>>> may
>>>>>> not know about PyCall.
>>>>>>
>>>>>>
>>>>>> On Friday, January 2, 2015 1:59:04 PM UTC-6, Douglas Bates wrote:
>>>>>>>
>>>>>>> For many statistics-oriented Julia users there is a great advantage
>>>>>>> in being able to piggy-back on R development and to use at least the
>>>>>>> data
>>>>>>> sets from R packages. Hence the RDatasets package and the read_rda
>>>>>>> function in the DataFrames package for reading saved R data.
>>>>>>>
>>>>>>> Over the last couple of days I have been experimenting with running
>>>>>>> an embedded R within Julia and calling R functions from Julia. This is
>>>>>>> similar in scope to the Rif package except that this code is written in
>>>>>>> Julia and not as a set of wrapper functions written in C. The R API is
>>>>>>> a C
>>>>>>> API and, in some ways, very simple. Everything in R is represented as a
>>>>>>> "symbolic expression" or SEXPREC and passed around as pointers to such
>>>>>>> expressions (called an SEXP type). Most functions take one or more
>>>>>>> SEXP
>>>>>>> values as arguments and return an SEXP.
>>>>>>>
>>>>>>> I have avoided reading the code for Rif for two reasons:
>>>>>>> 1. It is GPL3 licensed
>>>>>>> 2. I already know a fair bit of the R API and where to find API
>>>>>>> function signatures.
>>>>>>>
>>>>>>> Here's a simple example
>>>>>>> julia> initR()
>>>>>>> 1
>>>>>>>
>>>>>>> julia> globalEnv = unsafe_load(cglobal((:R_GlobalEnv,libR),SEXP),1)
>>>>>>> Ptr{Void} @0x0000000008c1c388
>>>>>>>
>>>>>>> julia> formaldehyde = tryEval(install(:Formaldehyde))
>>>>>>> Ptr{Void} @0x0000000008fd1d18
>>>>>>>
>>>>>>> julia> inherits(formaldehyde,"data.frame")
>>>>>>> true
>>>>>>>
>>>>>>> julia> printValue(formaldehyde)
>>>>>>> carb optden
>>>>>>> 1 0.1 0.086
>>>>>>> 2 0.3 0.269
>>>>>>> 3 0.5 0.446
>>>>>>> 4 0.6 0.538
>>>>>>> 5 0.7 0.626
>>>>>>> 6 0.9 0.782
>>>>>>>
>>>>>>> julia> length(formaldehyde)
>>>>>>> 2
>>>>>>>
>>>>>>> julia> names(formaldehyde)
>>>>>>> 2-element Array{ASCIIString,1}:
>>>>>>> "carb"
>>>>>>> "optden"
>>>>>>>
>>>>>>> julia> form1 = ccall((:VECTOR_ELT,libR),SEXP,
>>>>>>> (SEXP,Cint),formaldehyde,0)
>>>>>>> Ptr{Void} @0x000000000a5baf58
>>>>>>>
>>>>>>> julia> ccall((:TYPEOF,libR),Cint,(SEXP,),form1)
>>>>>>> 14
>>>>>>>
>>>>>>> julia> carb = copy(pointer_to_array(ccall((:
>>>>>>> REAL,libR),Ptr{Cdouble},(SEXP,),form1),length(form1)))
>>>>>>> 6-element Array{Float64,1}:
>>>>>>> 0.1
>>>>>>> 0.3
>>>>>>> 0.5
>>>>>>> 0.6
>>>>>>> 0.7
>>>>>>> 0.9
>>>>>>>
>>>>>>> julia> form2 = ccall((:VECTOR_ELT,libR),SEXP,
>>>>>>> (SEXP,Cint),formaldehyde,1)
>>>>>>> Ptr{Void} @0x000000000a5baef0
>>>>>>>
>>>>>>> julia> ccall((:TYPEOF,libR),Cint,(SEXP,),form2)
>>>>>>> 14
>>>>>>>
>>>>>>> julia> optden = copy(pointer_to_array(ccall((:
>>>>>>> REAL,libR),Ptr{Cdouble},(SEXP,),form2),length(form2)))
>>>>>>> 6-element Array{Float64,1}:
>>>>>>> 0.086
>>>>>>> 0.269
>>>>>>> 0.446
>>>>>>> 0.538
>>>>>>> 0.626
>>>>>>> 0.782
>>>>>>>
>>>>>>>
>>>>>>> A call to printValue uses the R printing mechanism.
>>>>>>>
>>>>>>> Questions:
>>>>>>> - What would be a good name for such a package? In the spirit of
>>>>>>> PyCall it could be RCall or Rcall perhaps.
>>>>>>>
>>>>>>> - Right now I am defining several functions that emulate the names
>>>>>>> of functions in R itself ir in the R API. What is a good balance?
>>>>>>> Obviously it would not be a good idea to bring in all the names in the
>>>>>>> R
>>>>>>> base namespace. On the other hand, those who know names like
>>>>>>> "inherits"
>>>>>>> and what it means in R will find it convenient to have such names in
>>>>>>> such a
>>>>>>> package.
>>>>>>>
>>>>>>> - Should I move the discussion the the julia-stats list?
>>>>>>>
>>>>>>>
>>>>>
>
