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reduce()
is an operation that combines the elements of a vector
into a single value. The combination is driven by .f
, a binary
function that takes two values and returns a single value: reducing
f
over 1:3
computes the value f(f(1, 2), 3)
.
reduce(.x, .f, ..., .init, .dir = c("forward", "backward"))reduce2(.x, .y, .f, ..., .init)
A list or atomic vector.
For reduce()
, a 2-argument function. The function will be passed
the accumulated value as the first argument and the "next" value as the
second argument.
For reduce2()
, a 3-argument function. The function will be passed the
accumulated value as the first argument, the next value of .x
as the
second argument, and the next value of .y
as the third argument.
The reduction terminates early if .f
returns a value wrapped in
a done()
.
Additional arguments passed on to the reduce function.
We now generally recommend against using ...
to pass additional
(constant) arguments to .f
. Instead use a shorthand anonymous function:
# Instead of
x |> reduce(f, 1, 2, collapse = ",")
# do:
x |> reduce(\(x, y) f(x, y, 1, 2, collapse = ","))
This makes it easier to understand which arguments belong to which function and will tend to yield better error messages.
If supplied, will be used as the first value to start
the accumulation, rather than using .x[[1]]
. This is useful if
you want to ensure that reduce
returns a correct value when .x
is empty. If missing, and .x
is empty, will throw an error.
The direction of reduction as a string, one of
"forward"
(the default) or "backward"
. See the section about
direction below.
For reduce2()
an additional
argument that is passed to .f
. If init
is not set, .y
should be 1 element shorter than .x
.
When .f
is an associative operation like +
or c()
, the
direction of reduction does not matter. For instance, reducing the
vector 1:3
with the binary function +
computes the sum ((1 + 2) + 3)
from the left, and the same sum (1 + (2 + 3))
from the
right.
In other cases, the direction has important consequences on the
reduced value. For instance, reducing a vector with list()
from
the left produces a left-leaning nested list (or tree), while
reducing list()
from the right produces a right-leaning list.
accumulate()
for a version that returns all intermediate
values of the reduction.
# Reducing `+` computes the sum of a vector while reducing `*`
# computes the product:
1:3 |> reduce(`+`)
1:10 |> reduce(`*`)
# By ignoring the input vector (nxt), you can turn output of one step into
# the input for the next. This code takes 10 steps of a random walk:
reduce(1:10, \(acc, nxt) acc + rnorm(1), .init = 0)
# When the operation is associative, the direction of reduction
# does not matter:
reduce(1:4, `+`)
reduce(1:4, `+`, .dir = "backward")
# However with non-associative operations, the reduced value will
# be different as a function of the direction. For instance,
# `list()` will create left-leaning lists when reducing from the
# right, and right-leaning lists otherwise:
str(reduce(1:4, list))
str(reduce(1:4, list, .dir = "backward"))
# reduce2() takes a ternary function and a second vector that is
# one element smaller than the first vector:
paste2 <- function(x, y, sep = ".") paste(x, y, sep = sep)
letters[1:4] |> reduce(paste2)
letters[1:4] |> reduce2(c("-", ".", "-"), paste2)
x <- list(c(0, 1), c(2, 3), c(4, 5))
y <- list(c(6, 7), c(8, 9))
reduce2(x, y, paste)
# You can shortcircuit a reduction and terminate it early by
# returning a value wrapped in a done(). In the following example
# we return early if the result-so-far, which is passed on the LHS,
# meets a condition:
paste3 <- function(out, input, sep = ".") {
if (nchar(out) > 4) {
return(done(out))
}
paste(out, input, sep = sep)
}
letters |> reduce(paste3)
# Here the early return branch checks the incoming inputs passed on
# the RHS:
paste4 <- function(out, input, sep = ".") {
if (input == "j") {
return(done(out))
}
paste(out, input, sep = sep)
}
letters |> reduce(paste4)
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