cut.trip: Split trip events into exact time-based boundaries.

In trip: Tracking Data

Split trip events into exact time-based boundaries.

Description

Split trip events within a single object into exact time boundaries, adding interpolated coordinates as required.

Usage

## S3 method for class 'trip'
cut(x, breaks, ...)

Arguments

x	A trip object.
breaks	A character string such as the breaks argument for cut.POSIXt, or alternatively a vector of date-time boundaries. (If the latter these must encompass all the time range of the entire trip object.)
...	Unused arguments.

Details

Motion between boundaries is assumed linear and extra coordinates are added at the cut points.

This function was completely rewritten in version 1.1-20.

Value

list of S4 trip objects, each with aligned boundaries in time based on cutting the input into intervals

A list of trip objects, named by the time boundary in which they lie.

Author(s)

Michael D. Sumner and Sebastian Luque

See Also

See also tripGrid.

Examples

set.seed(66)
d <- data.frame(x=1:100, y=rnorm(100, 1, 10),
                tms= as.POSIXct(as.character(Sys.time()), tz = "GMT") + c(seq(10, 1000, length=50),
                seq(100, 1500, length=50)), id=gl(2, 50))
sp::coordinates(d) <- ~x+y
tr <- trip(d, c("tms", "id"))

cut(tr, "200 sec")

bound.dates <- seq(min(tr$tms) - 1, max(tr$tms) + 1, length=5)
trip.list <- cut(tr, bound.dates)
bb <- sp::bbox(tr)
cn <- c(20, 8)
g <- sp::GridTopology(bb[, 1], apply(bb, 1, diff) / (cn - 1), cn)

tg <- tripGrid(tr, grid=g)
tg <- sp::as.image.SpatialGridDataFrame(tg)
tg$x <- tg$x - diff(tg$x[1:2]) / 2
tg$y <- tg$y - diff(tg$y[1:2]) / 2

op <- par(mfcol=c(4, 1))
for (i in 1:length(trip.list)) {
  plot(sp::coordinates(tr), pch=16, cex=0.7)
  title(names(trip.list)[i], cex.main=0.9)
  lines(trip.list[[i]])
  abline(h=tg$y, v=tg$x, col="grey")
  image(tripGrid(trip.list[[i]], grid=g), interpolate=FALSE,
  col=c("white", grey(seq(0.2, 0.7,  length=256))),add=TRUE)
  abline(h=tg$y, v=tg$x,  col="grey")
  lines(trip.list[[i]])
  points(trip.list[[i]], pch=16, cex=0.7)
}

par(op)
print("you may need to resize the window to see the grid data")

cn <- c(200, 80)
g <- sp::GridTopology(bb[, 1], apply(bb, 1, diff) / (cn - 1), cn)

tg <- tripGrid(tr, grid=g)
tg <- sp::as.image.SpatialGridDataFrame(tg)
tg$x <- tg$x - diff(tg$x[1:2]) / 2
tg$y <- tg$y - diff(tg$y[1:2]) / 2

op <- par(mfcol=c(4, 1))
for (i in 1:length(trip.list)) {
  plot(sp::coordinates(tr), pch=16, cex=0.7)
  title(names(trip.list)[i], cex.main=0.9)
  image(tripGrid(trip.list[[i]], grid=g, method="density", sigma=1),
        interpolate=FALSE,
        col=c("white", grey(seq(0.2, 0.7, length=256))),
        add=TRUE)
  lines(trip.list[[i]])
  points(trip.list[[i]], pch=16, cex=0.7)
}

par(op)
print("you may need to resize the window to see the grid data")



data("walrus818", package = "trip")
library(lubridate)
walrus_list <- cut(walrus818, seq(floor_date(min(walrus818$DataDT), "month"),
ceiling_date(max(walrus818$DataDT), "month"), by = "1 month"))
g <- rasterize(walrus818) * NA_real_
stk <- raster::stack(lapply(walrus_list, rasterize, grid = g))
st <- raster::aggregate(stk, fact = 4, fun = sum, na.rm = TRUE)
st[!st > 0] <- NA_real_

plot(st, col = oc.colors(52))

trip documentation built on July 9, 2023, 7:29 p.m.