check boolean expression in dataframe Rcpp (C )-CodePudding

I have a dataframe dat with data and a vector rule with logical rules

set.seed(124)
ro <- round(runif(n = 30,1,10),2)
dat <- as.data.frame(matrix(data =ro,ncol = 3)) ; colnames(dat) <- paste0("x" ,1:ncol(dat))
rule <- c("x1 > 5 & x2/2 > 2"  ,  "x1 > x2*2"  ,  "x3!=4")

I need to check if the expression is true

id <- 2
 for(i in 1:nrow(dat)){
   cr <- with(data = dat[i,] , expr = eval(parse(text = rule[id])))
   print(cr)
 }
[1] FALSE
[1] FALSE
[1] FALSE
[1] FALSE
[1] FALSE
[1] TRUE
[1] FALSE
[1] FALSE
[1] FALSE
[1] TRUE

How to do this with Rcpp ?

CodePudding user response：

Two things worth stressing here are

you do not need a low over all rows as R is vectorized, and that already fast
you can sweep the rules over your data and return a result matrix

Both of those are a one-liner:

> res <- do.call(cbind, lapply(rule, \(r) with(dat, eval(parse(text=r)))))
> res
       [,1]  [,2] [,3]
 [1,] FALSE FALSE TRUE
 [2,] FALSE FALSE TRUE
 [3,]  TRUE FALSE TRUE
 [4,] FALSE FALSE TRUE
 [5,] FALSE FALSE TRUE
 [6,] FALSE  TRUE TRUE
 [7,]  TRUE FALSE TRUE
 [8,]  TRUE FALSE TRUE
 [9,]  TRUE FALSE TRUE
[10,] FALSE  TRUE TRUE
>

(I used the R 4.1.* anonymous function there, you can relace \(r) with the standard function(r) as well.)

As this is already vectorised it will be faster than your per-row call, and even if you did it with Rcpp if would not be (much) faster than already vectorised code.