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## ---- eval = FALSE-------------------------------------------------------
# ## Note - this is R code.
# ## cppFunction in Rcpp allows rapid testing.
# require(Rcpp)
#
# cppFunction("
# NumericVector exfun(NumericVector x, int i){
# x = x*i;
# return x;
# }")
#
# exfun(1:5, 3)
#
# ## Use evalCpp to evaluate C++ expressions
# evalCpp("std::numeric_limits<double>::max()")
## ---- eval = FALSE-------------------------------------------------------
# # In R, create a package shell. For details,
# # see the "Writing R Extensions" manual and
# # the "Rcpp-package" vignette.
#
# Rcpp.package.skeleton("myPackage")
#
# # Add R code to pkg R/ directory. Call C++
# # function. Do type-checking in R.
#
# myfunR <- function(Rx, Ry) {
# ret = .Call("myCfun", Rx, Ry,
# package="myPackage")
# return(ret)
# }
## ---- eval=FALSE---------------------------------------------------------
# require(myPackage)
#
# aa <- 1.5
# bb <- 1.5
# cc <- myfunR(aa, bb)
# aa == bb
# # FALSE, C++ modifies aa
#
# aa <- 1:2
# bb <- 1:2
# cc <- myfunR(aa, bb)
# identical(aa, bb)
# # TRUE, R/C++ types don't match
# # so a copy was made
## ---- eval=FALSE---------------------------------------------------------
# Rcpp::sourceCpp("path/to/file/Rcpp_example.cpp")
# x <- 1:5
# all.equal(muRcpp(x), mean(x))
# all.equal(var(x),varRcpp(x))
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