將值分配給R中另一個環境中的對象的一部分

Question

假設我在環境e中定義了兩個類似的大對象x，y（datatable）。 我想用類似的方法改變x或y的很大一部分，而不用在f的執行環境中創建x或y的副本。例如：

e <- new.env() 
e$x <- c(1,2,3) # imagine this to be BIG (ie. dataframe with 200k vars each 500k rows) 
e$y <- c(4,5,6) # same here 
e$v <- 2  # minor variables 

f <- function(var_str, env, input){ 

    # do some computation on parts of var_str which is either "x" or "y" 
    # and store these right back into e$x or e$y, respectively. 
    # ie 

    str <- paste0(var_str,"[2:3] <- (",var_str,"[2:3])^2 + rep(v,2) + ", deparse(input1),"^3/c(100,101)") 
    eval(parse(text=str), envir= e) 

    # this does work but I can image there is an easier/more elegant way 
    # of doing this. 
} 

我想定義在全球環境的功能，該功能適用​​於E $ x和E $ y隨輸入不同的變量。 IE瀏覽器。執行

f("x", e, c(1,2)) 
f("y", e, c(3,4)) 

有沒有人有一個優雅的解決方案。

Answer 1

出於好奇，我試着用the simple example in the R6 tutorial工作以及與此想出了（複製作爲控制檯成績單）。我真的不知道它是否符合請求的非複製要求，但它似乎是在原地修改對象。

# Assumes one has created an R6 constructor named `RC` ... 
# slightly extended from the example in section 
RC <- setRefClass("RC", 
    fields = list(x = 'ANY'), 
    methods = list(
    getx = function() x, 
    setx = function(value) x <<- value, 
    setsub = function(i,j,val) x[i,j] <<- val 
) 
) 

#--- execution --- 
rc <- RC$new() 
rc$setx(matrix(1:20, 4,5)) 
rc 
# --- result ---  
Reference class object of class "RC" 

Field "x": 
    [,1] [,2] [,3] [,4] [,5] 
[1,] 1 5 9 13 17 
[2,] 2 6 10 14 18 
[3,] 3 7 11 15 19 
[4,] 4 8 12 16 20 

測試類特定的setsub功能：

rc$setsub(4,5,0) #Test of setting a single element within an object to a new value 
rc 
#-------  
Reference class object of class "RC" 
Field "x": 
    [,1] [,2] [,3] [,4] [,5] 
[1,] 1 5 9 13 17 
[2,] 2 6 10 14 18 
[3,] 3 7 11 15 19 
[4,] 4 8 12 16 0 

rc$setsub(1:4,1:4,0) #Test of setting a range of elements within an object to a new value 
rc 
# --------- 
Reference class object of class "RC" 
Field "x": 
    [,1] [,2] [,3] [,4] [,5] 
[1,] 0 0 0 0 17 
[2,] 0 0 0 0 18 
[3,] 0 0 0 0 19 
[4,] 0 0 0 0 0 

所以通過setsub這個（看得很輕測試）實施[<- -function的確實成功。使用self參考一個單一的努力來擴展這個例子確實失敗了。

Answer 2

eval(parse())是要避免的。您可以參考的環境是這樣的：

e <- new.env() 
e$x <- c(1,2,3) # imagine this to be BIG (ie. dataframe with 200k vars each 500k rows) 
e$y <- c(4,5,6) # same here 
e$v <- 2  # minor variables 

f <- function(var_str, env, input){ 

    # do some computation on parts of var_str which is either "x" or "y" 
    # and store these right back into e$x or e$y, respectively. 
    # ie 
    env[[var_str]][2:3] <- (env[[var_str]][2:3])^2 + rep(env$v,2) + input^3/input 

} 


f("x", e, 1:2) 
e$x 
#[1] 1 7 15