I don't know enough about the mechanics of your scenario to comment
intelligently, but I would in general agree with Dirk that if there is a
way to put something like this in a package that's the way it ought to be
done. You could certainly dispatch to different C++ functions within a
package using a variety of mechanisms including C++ templates, C-style
function pointers, etc. (the mechanics of doing so for your situation I'm
unsure of, but it should be possible).
On Thu, Apr 14, 2016 at 12:25 AM, Martin Lysy <ml...@uwaterloo.ca> wrote:
> Hello Dirk,
>
> For my specific purpose I have some reservations about package creation.
> Here is a description of the project I have in mind.
>
> I would like to use Rcpp to create a set of generic MCMC algorithms, into
> which a useR could easily hook their own target distributions written in
> C++ with minimal effort. For example, I would provide the following files:
>
> --------------------------------------
> GibbsSampler.cpp
>
> //[[Rcpp::export]]
> NumericMatrix GibbsSampler(int nIter, NumericVector xInit, List
> tuningParams) {
> // run some flavor of the Gibbs sampler
> }
> ---------------------------------------
> GibbsSampler.h
>
> double logDensity(NumericVector x);
> ---------------------------------------
>
> Then the useR would write MyDensityA.cpp, which contains the definition of
> logDensity, compile the three files, and have a Gibbs sampler for their
> specific density function written in C++ and ready to go in R. However, a
> useR might wish to use the GibbsSampler for a different density tomorrow.
> They would have a different definition of logDensity in MyDensityB.cpp.
> Ideally, the useR would have access to Gibbs samplers for both densities in
> the same R session.
>
> I can think of two ways of doing this with Rcpp:
>
> 1. Compile with sourceCpp (this is what I'm currently doing). There's
> the minor issue of giving separate R names to each Gibbs sampler, but there
> are many ways around that. The major issue is that sourceCpp only accepts
> a single .cpp file (or at least as far as my attempts were unsuccessful in
> the original post). So I'm stuck text-processing a bunch of .cpp and .h
> files together (the actual project I'm working on has about a dozen of
> each).
>
> 2. Compile an entire R package for each of MyDensityA and MyDensityB.
> However, it seems somewhat cumbersome to have a package loaded for every
> density function in the workspace. Moreover, naming conflicts are a bit
> more tricky. Right now (with sourceCpp), I'm using an interface of the form
>
> smpA <- gibbs.sampler(density = MyDensityA, niter = 1e4)
> smpB <- gibbs.sampler(density = MyDensityB, niter = 1e4)
>
> This is to align with things like lm(formula = MyModel). However, I can't
> quite see how to do this with separate packages loaded. Rather it seems
> I'd need something like
>
> smpA <- gibbs.sampler.MyDensityA(niter = 1e4)
> smpB <- gibbs.sampler.MyDensityB(niter = 1e4)
>
> However, to do this with packages I feel like I would still have to do
> some text replacement, which I'm already doing with the sourceCpp approach.
>
> In summary, I am not opposed to package creation, but I hope you can see
> my reservations at taking this route. Perhaps you could please suggest a
> way to achieve what I'm after with separate Rcpp packages for each density
> function. I take it from your reluctance to answer my original post that
> Rcpp only supports compilation of multiple files through the package
> creation protocol. I can think of many applications in which the useR
> could supply a minimal amount of C++ code (e.g., a log-likelihood function)
> to hook in with a large amount of code provided by the developer in order
> to speed things up considerably. So in my opinion it would be worthwhile
> to devise a mechanism to do this correctly.
>
> Best regards,
>
>
> Martin Lysy
> Assistant Professor of Statistics
> Department of Statistics and Actuarial Science
> University of Waterloo
>
> On Wed, Apr 13, 2016 at 5:34 PM, Dirk Eddelbuettel <e...@debian.org> wrote:
>
>>
>> Martin,
>>
>> Please please please look into creating a package.
>>
>> If you use RStudio: File -> New Project -> (New or Existing) Directory ->
>> Package and then select Rcpp.
>>
>> If not, consider install the (very tiny) pkgKitten package and call
>> Rcpp.package.skeleton() from Rcpp itself (but enhanced by pkgKitten if
>> present) for a saner package.
>>
>> Cheers, Dirk
>>
>> --
>> http://dirk.eddelbuettel.com | @eddelbuettel | e...@debian.org
>>
>
>
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