relist {utils} | R Documentation |
relist()
is an S3 generic function with a few methods in order
to allow easy inversion of unlist(obj)
when that is used
with an object obj
of (S3) class "relistable"
.
relist(flesh, skeleton) ## Default S3 method: relist(flesh, skeleton = attr(flesh, "skeleton")) ## S3 method for class 'factor': relist(flesh, skeleton = attr(flesh, "skeleton")) ## S3 method for class 'list': relist(flesh, skeleton = attr(flesh, "skeleton")) ## S3 method for class 'matrix': relist(flesh, skeleton = attr(flesh, "skeleton")) as.relistable(x) is.relistable(x) ## S3 method for class 'relistable': unlist(x, recursive = TRUE, use.names = TRUE)
flesh |
..... |
skeleton |
......... |
x |
an R object, typically a list (or vector). |
recursive |
logical. Should unlisting be applied to list
components of x ? |
use.names |
logical. Should names be preserved? |
Some functions need many parameters, which are most easily represented in
complex structures. Unfortunately, many mathematical functions in R,
including optim
and nlm
can only operate on
functions whose domain is
a vector. R has unlist()
to convert complex objects into a
vector representation. relist()
, it's methods and the
functionality mentioned here provide the inverse operation to convert
vectors back to the convenient structural representation.
This allows structured functions (such as optim()
) to have simple
mathematical interfaces.
For example, a likelihood function for a multivariate normal model needs a variance-covariance matrix and a mean vector. It would be most convenient to represent it as a list containing a vector and a matrix. A typical parameter might look like
list(mean=c(0, 1), vcov=cbind(c(1, 1), c(1, 0))).However,
optim
cannot operate on functions that take lists as input; it
only likes numeric vectors. The solution is conversion:
ipar <- list(mean=c(0, 1), vcov=cbind(c(1, 1), c(1, 0))) initial.param <- as.relistable(ipar) ll <- function(param.vector) { param <- relist(param.vector) -sum(dnorm(x, mean = param$mean, vcov = param$vcov, log = TRUE)) ## NB: dnorm() has no vcov... you should get the point } optim(unlist(initial.param), ll)
relist
takes two parameters: skeleton and flesh. Skeleton is a sample
object that has the right shape
but the wrong content. flesh
is a vector with the right content but the wrong shape. Invoking
relist(flesh, skeleton)will put the content of flesh on the skeleton. You don't need to specify skeleton explicitly if the skeleton is stored as an attribute inside flesh. In particular, flesh was created from some object obj with
unlist(as.relistable(obj))
then the skeleton attribute is automatically set.
As long as skeleton
has the right shape, it should be a precise inverse
of unlist
. These equalities hold:
relist(unlist(x), skeleton) == x unlist(relist(y, skeleton)) == y x <- as.relistable(x) relist(unlist(x)) == x
.....................
R Core, based on a code proposal by Andrew Clausen.
ipar <- list(mean=c(0, 1), vcov=cbind(c(1, 1), c(1, 0))) initial.param <- as.relistable(ipar) ul <- unlist(initial.param) relist(ul) stopifnot(identical(relist(ul), initial.param))