hop()
is the lower level engine that powers slide()
(at least in theory).
It has slightly different invariants than slide()
, and is useful
when you either need to hand craft boundary locations, or want to compute a
result with a size that is different from .x
.
hop(.x, .starts, .stops, .f, ...)hop_vec(.x, .starts, .stops, .f, ..., .ptype = NULL)
[vector]
The vector to iterate over and apply .f
to.
[integer]
Vectors of boundary locations that make up the windows to bucket .x
with.
Both .starts
and .stops
will be recycled to their common size, and
that common size will be the size of the result. Both vectors should be
integer locations along .x
, but out-of-bounds values are allowed.
[function / formula]
If a function, it is used as is.
If a formula, e.g. ~ .x + 2
, it is converted to a function. There
are three ways to refer to the arguments:
For a single argument function, use .
For a two argument function, use .x
and .y
For more arguments, use ..1
, ..2
, ..3
etc
This syntax allows you to create very compact anonymous functions.
Additional arguments passed on to the mapped function.
[vector(0) / NULL]
A prototype corresponding to the type of the output.
If NULL
, the default, the output type is determined by computing the
common type across the results of the calls to .f
.
If supplied, the result of each call to .f
will be cast to that type,
and the final output will have that type.
If getOption("vctrs.no_guessing")
is TRUE
, the .ptype
must be
supplied. This is a way to make production code demand fixed types.
A vector fulfilling the following invariants:
hop()
vec_size(hop(.x, .starts, .stops)) == vec_size_common(.starts, .stops)
vec_ptype(hop(.x, .starts, .stops)) == list()
hop_vec()
vec_size(hop_vec(.x, .starts, .stops)) == vec_size_common(.starts, .stops)
vec_size(hop_vec(.x, .starts, .stops)[[1]]) == 1L
vec_ptype(hop_vec(.x, .starts, .stops, .ptype = ptype)) == ptype
hop()
is very close to being a faster version of:
map2( .starts, .stops, function(start, stop) { x_slice <- vec_slice(.x, start:stop) .f(x_slice, ...) } )
Because of this, hop_index()
is often the more useful function. hop()
mainly exists for API completeness.
The main difference is that the start and stop values make up ranges of
possible locations along .x
, and it is not enforced that these locations
actually exist along .x
. As an example, with hop()
you can do the
following, which would be an error with vec_slice()
because 0L
is
out of bounds.
hop(c("a", "b"), .starts = 0L, .stops = 1L, ~.x) #> [[1]] #> [1] "a"
hop()
allows these out of bounds values to be fully compatible with
slide()
. It is always possible to construct a hop()
call from a slide()
call. For example, the following are equivalent:
slide(1:2, ~.x, .before = 1)hop(1:2, .starts = c(0, 1), .stops = c(1, 2), ~.x)
#> [[1]] #> [1] 1 #> #> [[2]] #> [1] 1 2
# NOT RUN {
# `hop()` let's you manually specify locations to apply `.f` at.
hop(1:3, .starts = c(1, 3), .stops = 3, ~.x)
# `hop()`'s start/stop locations are allowed to be out of bounds relative
# to the size of `.x`.
hop(
mtcars,
.starts = c(-1, 3),
.stops = c(2, 6),
~.x
)
# }
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