### 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()
%spacing
### Lifting from c(...) to list(...) or ...
# Some functions such as mean() take an atomic vector. It is often
# useful to transform them to functions taking a list. In the
# following example, we lift mean() to apply it to each row of a
# data frame. This works because a row is essentially a list of
# length-1 vectors:
mtcars %>% by_row(lift_vl(mean))
# In other situations we need the vector-valued function to take a
# variable number of arguments as with map_n(). This is a job for
# lift_vd():
map_n(mtcars, lift_vd(mean))
# lift_vd() will collect the arguments and concanete 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")
%spacing
### Lifting from list(...) to c(...) or ...
# cross_n() 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 <- lift_ld(cross_n)
out1 <- cross_n(list(a = 1:2, b = c("a", "b", "c")))
out2 <- cross(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 map_n() 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 %>% map_n(lift_ld(some, partial(`<`, 200)))
# Default arguments for ..f can be specified in the call to
# lift_ld()
lift_ld(cross_n, .filter = `==`)(1:3, 1:3) %>% str()
glue <- function(l) {
if (!is.list(l)) stop("not a list")
l %>% map_call(paste)
}
# This fails because glue() expects a list
letters %>% glue()
# Once shackled, glue() expects a vector
letters %>% lift_lv(glue)()
# The input type can be checked by specifying .type
letters %>% lift_lv(glue, .type = "numeric")() # fails
letters %>% lift_lv(glue, .type = "character")() # succeeds
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