Reduce uses a binary function to successively combine the elements of a given vector and a possibly given initial value. Filter extracts the elements of a vector for which a predicate (logical) function gives true. Find and Position give the first or last such element and its position in the vector, respectively. Map applies a function to the corresponding elements of given vectors. Negate creates the negation of a given function.
Reduce(f, x, init, right = FALSE, accumulate = FALSE)
Filter(f, x)
Find(f, x, right = FALSE, nomatch = NULL)
Map(f, ...)
Negate(f)
Position(f, x, right = FALSE, nomatch = NA_integer_)| Parameter | Description |
|---|---|
f |
a function of the appropriate arity (binary for Reduce, unary for Filter, Find and Position, \(k\)-ary for Map if this is called with \(k\) arguments). An arbitrary predicate function for Negate. |
x |
a vector. |
init |
an R object of the same kind as the elements of x. |
right |
a logical indicating whether to proceed from left to right (default) or from right to left. |
accumulate |
a logical indicating whether the successive reduce combinations should be accumulated. By default, only the final combination is used. |
nomatch |
the value to be returned in the case when “no match” (no element satisfying the predicate) is found. |
… |
vectors. |
# NOT RUN {
## A general-purpose adder:
add <- function(x) Reduce("+", x)
add(list(1, 2, 3))
## Like sum(), but can also used for adding matrices etc., as it will
## use the appropriate '+' method in each reduction step.
## More generally, many generics meant to work on arbitrarily many
## arguments can be defined via reduction:
FOO <- function(...) Reduce(FOO2, list(...))
FOO2 <- function(x, y) UseMethod("FOO2")
## FOO() methods can then be provided via FOO2() methods.
## A general-purpose cumulative adder:
cadd <- function(x) Reduce("+", x, accumulate = TRUE)
cadd(seq_len(7))
## A simple function to compute continued fractions:
cfrac <- function(x) Reduce(function(u, v) u + 1 / v, x, right = TRUE)
## Continued fraction approximation for pi:
cfrac(c(3, 7, 15, 1, 292))
## Continued fraction approximation for Euler's number (e):
cfrac(c(2, 1, 2, 1, 1, 4, 1, 1, 6, 1, 1, 8))
## Iterative function application:
Funcall <- function(f, ...) f(...)
## Compute log(exp(acos(cos(0))))
Reduce(Funcall, list(log, exp, acos, cos), 0, right = TRUE)
## n-fold iterate of a function, functional style:
Iterate <- function(f, n = 1)
function(x) Reduce(Funcall, rep.int(list(f), n), x, right = TRUE)
## Continued fraction approximation to the golden ratio:
Iterate(function(x) 1 + 1 / x, 30)(1)
## which is the same as
cfrac(rep.int(1, 31))
## Computing square root approximations for x as fixed points of the
## function t |-> (t + x / t) / 2, as a function of the initial value:
asqrt <- function(x, n) Iterate(function(t) (t + x / t) / 2, n)
asqrt(2, 30)(10) # Starting from a positive value => +sqrt(2)
asqrt(2, 30)(-1) # Starting from a negative value => -sqrt(2)
## A list of all functions in the base environment:
funs <- Filter(is.function, sapply(ls(baseenv()), get, baseenv()))
## Functions in base with more than 10 arguments:
names(Filter(function(f) length(formals(f)) > 10, funs))
## Number of functions in base with a '...' argument:
length(Filter(function(f)
any(names(formals(f)) %in% "..."),
funs))
# }
# NOT RUN {
## Find all objects in the base environment which are *not* functions:
Filter(Negate(is.function), sapply(ls(baseenv()), get, baseenv()))
# }