Lift the domain of a function
lift_xy()
is a composition helper. It helps you compose
functions by lifting their domain from a kind of input to another
kind. The domain can be changed from and to a list (l), a vector
(v) and dots (d). For example, lift_ld(fun)
transforms a
function taking a list to a function taking dots.
lift(..f, ..., .unnamed = FALSE) lift_dl(..f, ..., .unnamed = FALSE) lift_dv(..f, ..., .unnamed = FALSE) lift_vl(..f, ..., .type) lift_vd(..f, ..., .type) lift_ld(..f, ...) lift_lv(..f, ...)
..f |
A function to lift. |
... |
Default arguments for |
.unnamed |
If |
.type |
A vector mold or a string describing the type of the
input vectors. The latter can be any of the types returned by
|
The most important of those helpers is probably lift_dl()
because it allows you to transform a regular function to one that
takes a list. This is often essential for composition with purrr
functional tools. Since this is such a common function,
lift()
is provided as an alias for that operation.
A function.
list(...)
or c(...)
Here dots should be taken here in a figurative way. The lifted
functions does not need to take dots per se. The function is
simply wrapped a function in do.call()
, so instead
of taking multiple arguments, it takes a single named list or
vector which will be interpreted as its arguments. This is
particularly useful when you want to pass a row of a data frame
or a list to a function and don't want to manually pull it apart
in your function.
c(...)
to list(...)
or ...
These factories allow a function taking a vector to take a list
or dots instead. The lifted function internally transforms its
inputs back to an atomic vector. purrr does not obey the usual R
casting rules (e.g., c(1, "2")
produces a character
vector) and will produce an error if the types are not
compatible. Additionally, you can enforce a particular vector
type by supplying .type
.
lift_ld()
turns a function that takes a list into a
function that takes dots. lift_vd()
does the same with a
function that takes an atomic vector. These factory functions are
the inverse operations of lift_dl()
and lift_dv()
.
lift_vd()
internally coerces the inputs of ..f
to
an atomic vector. The details of this coercion can be controlled
with .type
.
### Lifting from ... to list(...) or c(...) x <- list(x = c(1:100, NA, 1000), na.rm = TRUE, trim = 0.9) lift_dl(mean)(x) # Or in a pipe: mean %>% lift_dl() %>% invoke(x) # You can also use the lift() alias for this common operation: lift(mean)(x) # Default arguments can also be specified directly in lift_dl() list(c(1:100, NA, 1000)) %>% lift_dl(mean, na.rm = TRUE)() # lift_dl() and lift_ld() are inverse of each other. # Here we transform sum() so that it takes a list fun <- sum %>% lift_dl() fun(list(3, NA, 4, na.rm = TRUE)) # Now we transform it back to a variadic function fun2 <- fun %>% lift_ld() fun2(3, NA, 4, na.rm = TRUE) # It can sometimes be useful to make sure the lifted function's # signature has no named parameters, as would be the case for a # function taking only dots. The lifted function will take a list # or vector but will not match its arguments to the names of the # input. For instance, if you give a data frame as input to your # lifted function, the names of the columns are probably not # related to the function signature and should be discarded. lifted_identical <- lift_dl(identical, .unnamed = TRUE) mtcars[c(1, 1)] %>% lifted_identical() mtcars[c(1, 2)] %>% lifted_identical() # ### Lifting from c(...) to list(...) or ... # In other situations we need the vector-valued function to take a # variable number of arguments as with pmap(). This is a job for # lift_vd(): pmap(mtcars, lift_vd(mean)) # lift_vd() will collect the arguments and concatenate them to a # vector before passing them to ..f. You can add a check to assert # the type of vector you expect: lift_vd(tolower, .type = character(1))("this", "is", "ok") # ### Lifting from list(...) to c(...) or ... # cross() normally takes a list of elements and returns their # cartesian product. By lifting it you can supply the arguments as # if it was a function taking dots: cross_dots <- lift_ld(cross) out1 <- cross(list(a = 1:2, b = c("a", "b", "c"))) out2 <- cross_dots(a = 1:2, b = c("a", "b", "c")) identical(out1, out2) # This kind of lifting is sometimes needed for function # composition. An example would be to use pmap() with a function # that takes a list. In the following, we use some() on each row of # a data frame to check they each contain at least one element # satisfying a condition: mtcars %>% pmap(lift_ld(some, partial(`<`, 200))) # Default arguments for ..f can be specified in the call to # lift_ld() lift_ld(cross, .filter = `==`)(1:3, 1:3) %>% str() # Here is another function taking a list and that we can update to # take a vector: glue <- function(l) { if (!is.list(l)) stop("not a list") l %>% invoke(paste, .) } ## Not run: letters %>% glue() # fails because glue() expects a list ## End(Not run) letters %>% lift_lv(glue)() # succeeds
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