如何修改 R 函数 lapply 中的 list/vector 参数？

Question

也许是一个奇怪的问题，但我有一个真实的用例：是否可以就地修改，即当函数运行而不是在副本上时，[=13 中的 list/vector 参数=] R 中的函数？如果是，该怎么做？由于一些（期望的）副作用，我需要它。更具体地说，在list/vector参数的每个元素被lapply'read'（或'used'）后，我需要删除它。

此致，

奥利维尔

一些代码来说明我在寻找什么。

Blocked 是一个原子向量，B 是一个列表。

Unblock <- function(M)
{
    Blocked[M] <<- FALSE
    Length_B_M <- length(B[[M]])
    if(Length_B_M > 0)
    {
        # Vectorised version
        UnblockAndUpdateAdjacencyList <- function(Node.Value)
        {
            Node.Name <- as.character(Node.Value)
            Node.Value <<- NULL # This is not correct because it won't delete the argument in place
            if(Blocked[Node.Name])  Unblock(Node.Name)
        }
        lapply(X = B[[M]], FUN = UnblockAndUpdateAdjacencyList)         
        # Unvectorised version
        # 'i' is a vector/list index - integer
        # Important: it is necessary to browse items backwards as items from the atomic vector 'B[[M]]' are deleted and thus its length decreases at each iteration
        for(i in Length_B_M:1)
        {
            P <- as.character(B[[M]][i])
            B[[M]] <<- B[[M]][-i]
            if(Blocked[P])  Unblock(P)
        }
    }
}

Answer 1

实际上我找到了一个稍微优雅的解决方案，即在 lapply.

的参数中没有任何显式循环和 vector/list 的任何副本

Unblock <- function(M)
    {
        Blocked[M] <<- FALSE
        Length_B_M <- length(B[[M]])
        if(Length_B_M > 0)
        {
            # Vectorised version
            # One solution is to copy the vector/list in the argument of 'lapply' - Actually not even needed
            UnblockAndUpdateAdjacencyList <- function(Node.Value)
            {
                Node.Name <- as.character(Node.Value)
                B[[M]] <<- B[[M]][-1]
                if(Blocked[Node.Name])  Unblock(Node.Name)
            }
            #B_M_copy <- B[[M]]
            #lapply(X = B_M_copy, FUN = UnblockAndUpdateAdjacencyList)
            lapply(X = B[[M]], FUN = UnblockAndUpdateAdjacencyList)
        }
    }

如何修改 R 函数 lapply 中的 list/vector 参数？

How to modify the list/vector argument in place in the R function lapply?

r

lapply