Suppose that A, B and C are matrices. And I have a list of them like this:
list(A,list(B,C))
I want to convert it to this:
list(A,B,C)
The unlist
function convert the matrices to vectors!
For example:
A=matrix(1:10,nrow=2)
B=list(A,list(A,A))
unlist(B)
To convert R List to Matrix, use the matrix() function and pass the unlist(list) as an argument. The unlist() method in R simplifies it to produce a vector that contains all the atomic components which occur in list data.
You can add lists as matrices in Python.
The list is one of the most versatile data types in R thanks to its ability to accommodate heterogenous elements. A single list can contain multiple elements, regardless of their types or whether these elements contain further nested data. So you can have a list of a list of a list of a list of a list …
Here is a recursive implementation:
flatten2 <- function(X) if(is.list(X)) Reduce(c, lapply(X, flatten2)) else list(X)
Then:
str(flatten2(B)) # list of three matrices:
# List of 3
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
And more complex:
C <- list(A, list(list(A, A), A))
str(flatten2(C))
# List of 4
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
# $ : int [1:2, 1:5] 1 2 3 4 5 6 7 8 9 10
Also, a "wordier" but faster version (this is the one tested by Pierre):
flatten <- function(X) {
res <- list()
for(i in X) res <- c(res, if(is.list(i)) Recall(i) else list(i))
res
}
You could also make flatten2
a little faster by replacing Reduce
with do.call
, but that is a little less cute. flatten
remains the fastest even with that change.
You could do something like this
delist<-function(x) {
lists <- sapply(x, class)=="list"
while(any(lists)) {
x<-mapply(function(y,z) if (!z) list(y) else (y), x, lists, SIMPLIFY=FALSE)
x<-do.call('c', x)
lists <- sapply(x, class)=="list"
}
x
}
with your example you get
delist(B)
# [[1]]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 1 3 5 7 9
# [2,] 2 4 6 8 10
#
# [[2]]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 1 3 5 7 9
# [2,] 2 4 6 8 10
#
# [[3]]
# [,1] [,2] [,3] [,4] [,5]
# [1,] 1 3 5 7 9
# [2,] 2 4 6 8 10
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