C ++或Rcpp：无循环的两个向量的比较

Question

I am a novice in C++ and Rcpp, and I am wondering how to compare each element of two different vectors without loop at one time.

My goal is to change the element of v1 by referencing other vector.`

Current code is

v1 = {6,7,8,9,10}
v2 = {2,4,6,8,10}
v3 = {a,b,a,b,c}
v4 = {0,0,0,0,0}
v5 = {a,b,c}
v6 = {1,2,3}

for (i in 1:5){
  if (v1[i] > v2[i]){
    for (j in 1:3){
      if (v5[j] == v3[i]){
        v4[i] = v2[i] + v6[j]
          if (v1[i] > v4[i]){
            v1[i] = v4[i]
          }
      }
    }
  }
}  

The result sould be

v1 = {3,6,7,9,10}

In fact, v1, v2, v3, v4 and v5, v6 are the different dataframe in R. Each element of v1 is compared to v2 . If an element i in v1 is larger than i element in v2 , the element of v1 becomes a sum of i element of v1 and element of v6 by corresponding v3 & v5 . Then the newly estimated value v4[i] is compared to v1[i] .

I have ta large number of cases in v1~v5 and v5~v6 . In this case, using loop takes a long time. Is it possible to compare the different vectors without loop? or how to estimate and reference the other vector's element?

Answer 1

I do not see the need to use Rcpp or C++ here. The way I understand your requirements, you are trying to manipulate two sets of equal length vectors. For a "set of equal length" vectors one normally uses a data.frame or one of its extensions. Here I am using base R, data.table and dplyr with tibble . See for yourself which syntax you prefer. Generally speaking, data.table will most likely be faster for large data sets.

Setup data:

v1 <- c(6,7,8,9,10)
v2 <- c(2,4,6,8,10)
v3 <- c("a","b","a","b","c")
v5 <- c("a","b","c")
v6 <- c(1,2,3)

Base R:

df1 <- data.frame(v1, v2, v3)
df2 <- data.frame(v5, v6)

df1 <- merge(df1, df2, by.x = "v3", by = "v5")
df1$v4 <- df1$v2 + df1$v6
df1$v1 <- ifelse(df1$v1 > df1$v2 & df1$v1 > df1$v4, df1[["v4"]], df1[["v1"]])
df1
#>   v3 v1 v2 v6 v4
#> 1  a  3  2  1  3
#> 2  a  7  6  1  7
#> 3  b  6  4  2  6
#> 4  b  9  8  2 10
#> 5  c 10 10  3 13

data.table :

library(data.table)
dt1 <- data.table(v1, v2, v3, key = "v3")
dt2 <- data.table(v5, v6, key = "v5")

dt1[dt2, v4 := v2 + v6]
dt1[v1 > v2 & v1 > v4, v1 := v4]
dt1
#>    v1 v2 v3 v4
#> 1:  3  2  a  3
#> 2:  7  6  a  7
#> 3:  6  4  b  6
#> 4:  9  8  b 10
#> 5: 10 10  c 13

dplyr :

suppressPackageStartupMessages(library(dplyr))
t1 <- tibble(v1, v2, v3)
t2 <- tibble(v5, v6)
t1 %>% 
  inner_join(t2, by = c("v3" = "v5")) %>%
  mutate(v4 = v2 + v6) %>%
  mutate(v1 = case_when(
    v1 > v2 & v1 > v4 ~ v4,
    TRUE ~ v1
  ))
#> # A tibble: 5 x 5
#>      v1    v2 v3       v6    v4
#>   <dbl> <dbl> <chr> <dbl> <dbl>
#> 1     3     2 a         1     3
#> 2     6     4 b         2     6
#> 3     7     6 a         1     7
#> 4     9     8 b         2    10
#> 5    10    10 c         3    13

^{Created on 2019-04-19 by the reprex package (v0.2.1)}

The general idea is always the same:

• join the two tables on the character column
• create new column v4 as sum of v2 and v6
• update v1 to the value of v4 where v1 > v2 and v1 > v4

Note that base R and data.table do not preserve the order, so it would make more sense to put the output into an additional column.