Hello,
As a follow up on this thread, I've now commited a lazy version of
sapply. It can be used with a functor that has a nested result_type
type, or raw functions as illustrated by these examples from the unit
tests:
test.sugar.sapply <- function( ){
inc <- '
template <typename T>
class square : public std::unary_function<T,T> {
public:
T operator()( T t) const { return t*t ; }
} ;
'
fx <- cxxfunction( signature( x = "numeric" ), '
NumericVector xx(x) ;
NumericVector res = sapply( xx, square<double>() );
return res ;
', include = inc, plugin = "Rcpp" )
checkEquals( fx(1:10) , (1:10)^2 )
}
test.sugar.sapply.rawfun <- function( ){
inc <- '
double square( double x){ return x*x; }
'
fx <- cxxfunction( signature( x = "numeric" ), '
NumericVector xx(x) ;
NumericVector res = sapply( xx, square );
return res ;
', include = inc, plugin = "Rcpp" )
checkEquals( fx(1:10) , (1:10)^2 )
}
There is one more thing since this thread, sapply uses the new
Rcpp::traits::result_of trait to find out the result type of the function.
namespace Rcpp{
namespace traits{
template <typename T>
struct result_of{
typedef typename T::result_type type ;
} ;
template <typename RESULT_TYPE, typename INPUT_TYPE>
struct result_of< RESULT_TYPE (*)(INPUT_TYPE) >{
typedef RESULT_TYPE type ;
} ;
}
}
This version of sapply is lazy, so for example this works :
test.sugar.sapply.square <- function( ){
inc <- '
template <typename T>
class square : public std::unary_function<T,T> {
public:
T operator()( T t) const { return t*t ; }
} ;
'
fx <- cxxfunction( signature( x = "numeric" ), '
NumericVector xx(x) ;
return all( sapply( xx * xx , square<double>() ) < 10 );
', include = inc, plugin = "Rcpp" )
checkTrue( fx(1:10) )
}
and sapply only needs to calculate square( xx[0] * xx[0] ) and square(
xx[1] * xx[1] ) to make its final decision.
Romain
Le 16/06/10 14:58, Douglas Bates a écrit :
Ever since I read Phil Spector's book on S I have been a fan of
functional programming in S and R. When Jose Pinheiro and I were
working on the nlme package there was a joke between us that you could
tell which of us wrote which parts of the code because his parts
always had an object named "aux" and my parts always had
"unlist(lapply(list(...)))".
Even within C++ I like to use the std:: algorithms like
std::transform, but, of course, there are differences between a
strongly typed language like C++ and a dynamically typed language like
S. Templates can get around these differences to some extent but I am
still a bit of a novice regarding templates.
Currently I want to apply some functions to lists but entirely within
the C++ code (i.e. I don't want to create Rcpp Function objects and
call back to R). For the sake of argument, consider a function that
extracts the lengths of the components of the lists.
library(Rcpp)
library(inline)
inc<- '
class length {
public:
R_len_t operator() (RObject const& x) {return Rf_length(SEXP(x));}
};
'
code<- '
List lst(ll);
IntegerVector ans(lst.size());
std::transform(lst.begin(), lst.end(), ans.begin(), length());
return ans;
'
ltst<- cxxfunction(signature(ll = "list"), code, "Rcpp", inc)
ll<- list(a = numeric(0), b = LETTERS[6:9], c = c)
ltst(ll)
sapply(ll, length)
I would like to create a templated sapply function like
template<int RTYPE>
Vector<RTYPE> sapply(List ll, ??) {
Vector<RTYPE> ans(ll.size());
CharacterVector nms = ll.names();
if (nms.size() == ll.size()) ans.names() = nms;
std::transform(ll.begin(), ll.end(), ans.begin(), ??);
return ans;
}
but I don't know how to specify the second argument that is a function
that returns the atomic element type of a Vector<RTYPE> (is this as
simple as Vector<RTYPE>::value_type?) and has a single argument which
probably should be an RObject (although might be an SEXP, if that was
more convenient). Can someone (probably Romain) provide some
guidance?
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--
Romain Francois
Professional R Enthusiast
+33(0) 6 28 91 30 30
http://romainfrancois.blog.free.fr
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