c++ - Getting user input from R console: Rcpp and std::cin -


i have been doing exercises learn c++ , decided integrate them r since want write c++ backends r functions. having trouble finding solution retrieve user input r console. while there rcpp::rcout printing , returning output, there doesn't seem similar funciton std::cin.... 

#include <rcpp.h> // [[rcpp::export]] rcpp::string cola() {   rcpp::rcout << "pick drink:" << std::endl << "1 - espresso" << std::endl << "2 - americano" << std::endl << "3 - latte" << std::endl << "4 - cafe dopio" <<  std::endl << "5 - tea" << std::endl;   int drink;   std::cin >> drink;   std::string out;   switch(drink) {   case 1: out = "here espresso";   case 2: out = "here americano";   case 3: out = "here latte";   case 4: out = "here cafe dopio";   case 5: out = "here tea";   case 0: out = "error. choice not valid, here money back.";     break;   default:     if(drink > 5) {out = "error. choice not valid, here money back.";}   }   return out; }

even without rcpp in mix, std::cin unsuitable interactive input.

to use r console rcpp, need use r functions (in particular, readline) instead of c++ functionality. luckily can pull r objects c++ code:

environment base = environment("package:base"); function readline = base["readline"]; function as_numeric = base["as.numeric"];

and can use them:

int drink = as<int>(as_numeric(readline("> ")));

beware there's error in code: cases fall-through since missing break; furthermore, there’s no reason have case 0, , there’s no reason @ if in default case.

oh, , finally, don’t use std::endl unless need flush output (and need once here, @ end); use '\n' instead.


Comments

Post a Comment

Popular posts from this blog

python - Best design pattern for collection of objects -

i have following architecture: +-----------------+ | collection | | | | | | | | | +-----------------+ | ^ | | create() | | | | v | getitem(b) +------------+ | | item | | | | | | +------+ | | +------------+ a class managing collection of items, creates items. , these items may need other items collection. the actual code in python, , collection passes parameter created item . see it, bad practice. improvement can see pass few functions of collection needed item , instead of whole instance. for example: class collection: getitem(self, id): ... createitem(self, id): item = item(id, self) # <-- pass self ... class item: __init__(self, id, col): ... col.getite...
Read more

go - serving up pdfs using golang -

Image
just wondering if guys can code. it works serving images not pdf brochure. in advance func main(){ http.handlefunc("/", func(w http.responsewriter, r *http.request){ filename := "/var/www/filedipenser/brochure.pdf" streampdfbytes, err := ioutil.readfile( filename ) if err != nil { fmt.println(err) os.exit(1) } b := bytes.newbuffer(streampdfbytes) w.header().set("content-type", "application/pdf") if _, err := b.writeto(w); err != nil { fmt.fprintf(w, "%s", err) } w.write([]byte("pdf generated")) }) err := http.listenandserve(":4111", nil) if err != nil { log.fatal("listenandserve: ", err) fmt.println(err) } } the code bit inefficient appears working. however, pdf viewers might sensitive extraneous output adding end of http response stream...
Read more

r - Using `bbmle:mle2` with vector parameters (already works using `optim`) -

i having trouble using bbmle:mle2 function when trying regression. illustrate problem, have come toy example. we define minus log-likelihood poisson distribution (or custom distribution): ll <- function(beta, z, x){ -sum(stats::dpois(x, lambda = exp(z %*% beta), log = true)) } in code above, beta parameter vector estimate, z model/design matrix , x variable of interest. i generate random data work with: set.seed(2) age <- round(exp(rnorm(5000, mean = 2.37, sd = 0.78) - 1)) claim <- rpois(5000, lambda = 0.07 i can use optim regression. here intercept model: z1 <- model.matrix(claim ~ 1) optim(par = 0, fn = ll, z = z1, x = claim) here intercept + age model: z2 <- model.matrix(claim ~ age) optim(par = c(0, 0), fn = ll, z = z2, x = claim) the way large number of different models can assessed quite easy, 1 has specify model matrix. how can made work mle2 function bbmle package? i can it, if beta one-dimensional: mle2(minuslogl = functio...
Read more