条件向量化到向量命名列表的匹配

Question

I have a named list of vectors, y. The names of the list correspond to the values of variable, x. I need to return the value of the vector in y that matches the value of x at position i. For example, if x == "b" at index 25, I expect to return the 25th value of the "b" vector contained in the list y.

This is my current solution:

x <- sample(letters[1:4], 100, replace = T)

y <- list("a"=rnorm(100), "b"=rnorm(100), "c"=rnorm(100))

i <- match(x, names(y))
m <- sapply(i, function(i) {out <- rep(0,3); out[i] <- 1; out})

final <- apply(t(m) * do.call(cbind, y), 1, sum)

I am hoping for something more idiomatic. As part of the solution, the answer handle cases where values in x do not appear in the names of y.

The real world use case I am trying to solve is the case where I have several segmented model predictions applied to the entire population that I need to assign to their appropriate segment.

EDIT Also, trying to avoid the clunky usage of ifelse . Since the names are known, I shouldn't have to specify them manually.

Answer 1

使用带有二维索引的矩阵子集，您可以简单地执行

do.call(cbind, y)[cbind(1:length(i), i)]