iv-splits | R Documentation |
This family of functions revolves around splitting an iv on its endpoints, which results in a new iv that is entirely disjoint (i.e. non-overlapping). The intervals in the resulting iv are known as "splits".
iv_splits()
computes the disjoint splits for x
.
iv_identify_splits()
identifies the splits that correspond to each
interval in x
. It replaces x
with a list of the same size where each
element of the list contains the splits that the corresponding interval in
x
overlaps. This is particularly useful alongside tidyr::unnest()
.
iv_locate_splits()
returns a two column data frame with a key
column
containing the result of iv_splits()
and a loc
list-column containing
integer vectors that map each interval in x
to the splits that it overlaps.
iv_splits(x, ..., on = NULL)
iv_identify_splits(x, ..., on = NULL)
iv_locate_splits(x, ..., on = NULL)
x |
An interval vector. |
... |
These dots are for future extensions and must be empty. |
on |
An optional vector of additional values to split on. This should have the same type as |
For iv_splits()
, an iv with the same type as x
.
For iv_identify_splits()
, a list-of containing ivs with the same size as
x
.
For iv_locate_splits()
, a two column data frame with a key
column
of the same type as x
and loc
list-column containing integer vectors.
Graphically, generating splits looks like:
library(tidyr)
library(dplyr)
# Guests to a party and their arrival/departure times
guests <- tibble(
arrive = as.POSIXct(
c("2008-05-20 19:30:00", "2008-05-20 20:10:00", "2008-05-20 22:15:00"),
tz = "UTC"
),
depart = as.POSIXct(
c("2008-05-20 23:00:00", "2008-05-21 00:00:00", "2008-05-21 00:30:00"),
tz = "UTC"
),
name = list(
c("Mary", "Harry"),
c("Diana", "Susan"),
"Peter"
)
)
guests <- unnest(guests, name) %>%
mutate(iv = iv(arrive, depart), .keep = "unused")
guests
# You can determine the disjoint intervals at which people
# arrived/departed with `iv_splits()`
iv_splits(guests$iv)
# Say you'd like to determine who was at the party at any given time
# throughout the night
guests <- mutate(guests, splits = iv_identify_splits(iv))
guests
# Unnest the splits to generate disjoint intervals for each guest
guests <- guests %>%
unnest(splits) %>%
select(name, splits)
guests
# Tabulate who was there at any given time
guests %>%
summarise(n = n(), who = list(name), .by = splits)
# ---------------------------------------------------------------------------
x <- iv_pairs(c(1, 5), c(4, 9), c(12, 15))
x
# You can provide additional singular values to split on with `on`
iv_splits(x, on = c(2, 13))
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