Convert a foreign object to an sftime object
Usage
st_as_sftime(x, ...)
# S3 method for class 'ST'
st_as_sftime(x, ...)
# S3 method for class 'Track'
st_as_sftime(x, ...)
# S3 method for class 'Tracks'
st_as_sftime(x, ...)
# S3 method for class 'TracksCollection'
st_as_sftime(x, ...)
# S3 method for class 'sftime'
st_as_sftime(x, ...)
# S3 method for class 'sf'
st_as_sftime(x, ..., time_column_name = NULL)
# S3 method for class 'stars'
st_as_sftime(x, ..., long = TRUE, time_column_name = NULL)
# S3 method for class 'data.frame'
st_as_sftime(
x,
...,
agr = NA_agr_,
coords,
wkt,
dim = "XYZ",
remove = TRUE,
na.fail = TRUE,
sf_column_name = NULL,
time_column_name = NULL,
time_column_last = FALSE
)
# S3 method for class 'ppp'
st_as_sftime(x, ..., time_column_name)
# S3 method for class 'psp'
st_as_sftime(x, ..., time_column_name)
# S3 method for class 'lpp'
st_as_sftime(x, ..., time_column_name)
# S3 method for class 'sftrack'
st_as_sftime(x, ...)
# S3 method for class 'sftraj'
st_as_sftime(x, ...)
# S3 method for class 'cubble_df'
st_as_sftime(x, ..., sfc = NULL, crs, silent = FALSE)Arguments
- x
An object to be converted into an object of class
sftime.- ...
Further arguments passed to methods.
- time_column_name
A character value; name of the active time column. In case there is more than one and
time_column_nameisNULL, the first one is taken.- long
A logical value; See
st_as_sf. Typically,longshould be set toTRUEsince time information typically is a dimension of astarsobject.- agr
A character vector; see the details section of
st_sf.- coords
In case of point data: names or numbers of the numeric columns holding coordinates.
- wkt
The name or number of the character column that holds WKT encoded geometries.
- dim
Passed on to
st_point(only when argumentcoordsis given).- remove
A logical value; when
coordsorwktis given, remove these columns fromx?- na.fail
A logical value; if
TRUE, raise an error if coordinates contain missing values.- sf_column_name
A character value; name of the active list-column with simple feature geometries; in case there is more than one and
sf_column_nameisNULL, the first one is taken.- time_column_last
A logical value; if
TRUE, the active time column is always put last, otherwise column order is left unmodified. If bothsfc_lastandtime_column_lastareTRUE, the active time column is put last.- sfc
object of class
sfc(see package sf)- crs
Coordinate reference system, something suitable as input to
st_crs.- silent
logical; suppress message?
Value
x converted to an sftime object.
st_as_sftime.Tracks furthermore adds a column
track_name with the names of the tracks slot of the input
Tracks object.
st_as_sftime.TracksCollection furthermore adds the columns
tracks_name with the names of the tracksCollection slot and
track_name with the names of the tracks slot of the input
Tracks object.
Examples
# modified from spacetime:
library(sp)
library(spacetime)
sp <- cbind(x = c(0,0,1), y = c(0,1,1))
row.names(sp) <- paste("point", 1:nrow(sp), sep="")
sp <- SpatialPoints(sp)
time <- as.POSIXct("2010-08-05") + 3600 * (10:12)
x <- STI(sp, time)
st_as_sftime(x)
#> Warning: 'tzone' attributes are inconsistent
#> Spatiotemporal feature collection with 3 features and 0 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: 0 ymin: 0 xmax: 1 ymax: 1
#> CRS: NA
#> Time column with classes: 'POSIXct', 'POSIXt'.
#> Ranging from 2010-08-05 10:00:00 to 2010-08-05 12:00:00.
#> st_as_sfc.x.sp. time
#> 1 POINT (0 0) 2010-08-05 10:00:00
#> 2 POINT (0 1) 2010-08-05 11:00:00
#> 3 POINT (1 1) 2010-08-05 12:00:00
# convert a Track object from package trajectories to an sftime object
library(trajectories)
x1_Track <- trajectories::rTrack(n = 100)
x1_Track@data$speed <- sort(rnorm(length(x1_Track)))
x1_sftime <- st_as_sftime(x1_Track)
#> Warning: 'tzone' attributes are inconsistent
# convert a Tracks object from package trajectories to an sftime object
x2_Tracks <- trajectories::rTracks(m = 6)
x2_sftime <- st_as_sftime(x2_Tracks)
#> Warning: 'tzone' attributes are inconsistent
# convert a TracksCollection object from package trajectories to an sftime object
x3_TracksCollection <- trajectories::rTracksCollection(p = 2, m = 3, n = 50)
x3_sftime <- st_as_sftime(x3_TracksCollection)
#> Warning: 'tzone' attributes are inconsistent
# convert an sftime object to an sftime object
st_as_sftime(x3_sftime)
#> Spatiotemporal feature collection with 300 features and 3 fields
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -57.87874 ymin: -105.2126 xmax: 15.68272 ymax: 40.13782
#> CRS: NA
#> Time column with classes: 'POSIXct', 'POSIXt'.
#> Ranging from 1970-01-01 to 1970-01-01 04:49:00.
#> First 10 features:
#> ones tracks_name track_name st_as_sfc.x.sp. time
#> 1 1 Tracks1 Track1 POINT (0.8546559 -1.036985) 1970-01-01 00:00:00
#> 2 1 Tracks1 Track1 POINT (0.2559254 1.134189) 1970-01-01 00:00:00
#> 3 1 Tracks1 Track1 POINT (0.7723814 -2.861054) 1970-01-01 00:01:00
#> 4 1 Tracks1 Track1 POINT (-0.578062 1.354914) 1970-01-01 00:01:00
#> 5 1 Tracks1 Track1 POINT (0.4824357 -4.520175) 1970-01-01 00:02:00
#> 6 1 Tracks1 Track1 POINT (-2.030241 2.319898) 1970-01-01 00:02:00
#> 7 1 Tracks1 Track1 POINT (1.821826 -6.1945) 1970-01-01 00:03:00
#> 8 1 Tracks1 Track1 POINT (-1.977036 3.783254) 1970-01-01 00:03:00
#> 9 1 Tracks1 Track1 POINT (1.765991 -6.699866) 1970-01-01 00:04:00
#> 10 1 Tracks1 Track1 POINT (-2.123454 6.196938) 1970-01-01 00:04:00
# convert an sf object to an sftime object
g <- st_sfc(st_point(c(1, 2)), st_point(c(1, 3)), st_point(c(2, 3)),
st_point(c(2, 1)), st_point(c(3, 1)))
x4_sf <- st_sf(a = 1:5, g, time = Sys.time() + 1:5)
x4_sftime <- st_as_sftime(x4_sf)
# convert a Tracks object from package trajectories to an sftime object
x5_stars <- stars::read_stars(system.file("nc/bcsd_obs_1999.nc", package = "stars"))
#> pr, tas,
x5_sftime <- st_as_sftime(x5_stars, time_column_name = "time")
# this requires some thought to not accidentally drop time dimensions. For
# example, setting `merge = TRUE` will drop the time dimension and thus throw
# an error:
if (FALSE) { # \dontrun{
x5_sftime <- st_as_sftime(x5_stars, merge = TRUE, time_column_name = "time")
} # }
# convert a data frame to an sftime object
x5_df <-
data.frame(a = 1:5, g, time = Sys.time() + 1:5, stringsAsFactors = FALSE)
x5_sftime <- st_as_sftime(x5_df)
# convert a ppp object to an sftime object (modified from the sf package)
if (require(spatstat.geom)) {
st_as_sftime(gorillas, time_column_name = "date")
}
#> Loading required package: spatstat.geom
#> Loading required package: spatstat.data
#> Loading required package: spatstat.univar
#> spatstat.univar 3.0-1
#> spatstat.geom 3.3-2
#> Spatiotemporal feature collection with 648 features and 3 fields
#> Geometry type: GEOMETRY
#> Dimension: XY
#> Bounding box: xmin: 580457.9 ymin: 674172.8 xmax: 585934 ymax: 678739.2
#> CRS: NA
#> Time column with class: 'Date'.
#> Ranging from 2006-01-06 to 2009-05-31.
#> First 10 features:
#> group season label geom date
#> NA <NA> <NA> window POLYGON ((584712 674237.1, ... <NA>
#> 1 major dry point POINT (582518.4 676886.2) 2006-01-06
#> 2 major dry point POINT (581823 677422.7) 2006-01-10
#> 3 major dry point POINT (582131 676937.9) 2006-01-15
#> 4 major dry point POINT (582111.9 677420) 2006-01-24
#> 5 minor dry point POINT (582585.1 677509.7) 2006-01-27
#> 6 major dry point POINT (582302.3 677521.6) 2006-01-28
#> 7 major dry point POINT (583167.2 676730.5) 2006-02-01
#> 8 major dry point POINT (583584.5 677207.1) 2006-02-03
#> 9 major dry point POINT (583117.8 676850.3) 2006-02-13
# convert a psp object to an sftime object (modified from the spatstat.geom
# package)
if (require(spatstat.geom)) {
# modified from spatstat.geom:
x_psp <-
psp(
runif(10), runif(10), runif(10), runif(10), window=owin(),
marks = data.frame(time = Sys.time() + 1:10)
)
st_as_sftime(x_psp, time_column_name = "time")
}
#> Spatiotemporal feature collection with 11 features and 1 field
#> Geometry type: GEOMETRY
#> Dimension: XY
#> Bounding box: xmin: 0 ymin: 0 xmax: 1 ymax: 1
#> CRS: NA
#> Time column with classes: 'POSIXct', 'POSIXt'.
#> Ranging from 2024-09-13 09:15:14.847379 to 2024-09-13 09:15:23.847379.
#> First 10 features:
#> label geom time
#> NA window POLYGON ((0 0, 1 0, 1 1, 0 ... <NA>
#> 1 segment LINESTRING (0.3203339 0.798... 2024-09-13 09:15:14
#> 2 segment LINESTRING (0.4039816 0.366... 2024-09-13 09:15:15
#> 3 segment LINESTRING (0.03262274 0.38... 2024-09-13 09:15:16
#> 4 segment LINESTRING (0.4922266 0.673... 2024-09-13 09:15:17
#> 5 segment LINESTRING (0.1416749 0.439... 2024-09-13 09:15:18
#> 6 segment LINESTRING (0.7991584 0.712... 2024-09-13 09:15:19
#> 7 segment LINESTRING (0.4091124 0.435... 2024-09-13 09:15:20
#> 8 segment LINESTRING (0.9364347 0.665... 2024-09-13 09:15:21
#> 9 segment LINESTRING (0.7329098 0.523... 2024-09-13 09:15:22
# convert an lpp object to an sftime object (modified from the
# spatstat.linnet package)
if (require(spatstat.geom) && require(spatstat.linnet)) {
# modified from spatstat.linnet:
# letter 'A'
v <- spatstat.geom::ppp(x=(-2):2, y=3*c(0,1,2,1,0), c(-3,3), c(-1,7))
edg <- cbind(1:4, 2:5)
edg <- rbind(edg, c(2,4))
letterA <- spatstat.linnet::linnet(v, edges=edg)
# points on letter A
xx <-
spatstat.geom::ppp(
x=c(-1.5,0,0.5,1.5), y=c(1.5,3,4.5,1.5),
marks = data.frame(time = Sys.time() + 1:4, a = 1:4),
window = spatstat.geom::owin(
xrange = range(c(-1.5,0,0.5,1.5)),
yrange = range(c(1.5,3,4.5,1.5)))
)
x_lpp <- spatstat.linnet::lpp(xx, letterA)
# convert to sftime
st_as_sftime(x_lpp, time_column_name = "time")
}
#> Loading required package: spatstat.linnet
#> Loading required package: spatstat.random
#> spatstat.random 3.3-1
#> Loading required package: spatstat.explore
#> Loading required package: nlme
#>
#> Attaching package: ‘nlme’
#> The following object is masked from ‘package:dplyr’:
#>
#> collapse
#> spatstat.explore 3.3-2
#> Loading required package: spatstat.model
#> Loading required package: rpart
#> spatstat.model 3.3-1
#> spatstat.linnet 3.2-1
#> Spatiotemporal feature collection with 10 features and 4 fields
#> Geometry type: GEOMETRY
#> Dimension: XY
#> Bounding box: xmin: -3 ymin: -1 xmax: 3 ymax: 7
#> CRS: NA
#> Time column with classes: 'POSIXct', 'POSIXt'.
#> Ranging from 2024-09-13 09:15:15.070841 to 2024-09-13 09:15:18.070841.
#> label seg tp a geom time
#> 1 window NA NA NA POLYGON ((-3 -1, 3 -1, 3 7,... <NA>
#> 2 segment NA NA NA LINESTRING (-2 0, -1 3) <NA>
#> 3 segment NA NA NA LINESTRING (-1 3, 0 6) <NA>
#> 4 segment NA NA NA LINESTRING (0 6, 1 3) <NA>
#> 5 segment NA NA NA LINESTRING (1 3, 2 0) <NA>
#> 6 segment NA NA NA LINESTRING (-1 3, 1 3) <NA>
#> 7 point 1 0.5 1 POINT (-1.5 1.5) 2024-09-13 09:15:15
#> 8 point 5 0.5 2 POINT (0 3) 2024-09-13 09:15:16
#> 9 point 3 0.5 3 POINT (0.5 4.5) 2024-09-13 09:15:17
#> 10 point 4 0.5 4 POINT (1.5 1.5) 2024-09-13 09:15:18
# convert an sftrack object to an sftime object (modified from sftrack)
if (require(sftrack)) {
# get an sftrack object
data("raccoon")
raccoon$timestamp <- as.POSIXct(raccoon$timestamp, "EST")
burstz <-
list(id = raccoon$animal_id, month = as.POSIXlt(raccoon$timestamp)$mon)
x_sftrack <-
as_sftrack(raccoon,
group = burstz, time = "timestamp",
error = NA, coords = c("longitude", "latitude")
)
# convert to sftime
st_as_sftime(x_sftrack)
}
#> Loading required package: sftrack
#> Spatiotemporal feature collection with 445 features and 8 fields (with 168 geometries empty)
#> Geometry type: POINT
#> Dimension: XY
#> Bounding box: xmin: -80.28149 ymin: 26.06761 xmax: -80.27046 ymax: 26.07706
#> CRS: NA
#> Time column with classes: 'POSIXct', 'POSIXt'.
#> Ranging from 2019-01-18 19:02:30 to 2019-02-01 18:02:30.
#> First 10 features:
#> animal_id latitude longitude height hdop vdop fix sft_group
#> 1 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 2 TTP-058 26.06945 -80.27906 7 6.2 3.2 2D (id: TTP-058, month: 0)
#> 3 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 4 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 5 TTP-058 26.06769 -80.27431 858 5.1 3.2 2D (id: TTP-058, month: 0)
#> 6 TTP-058 26.06867 -80.27930 350 1.9 3.2 3D (id: TTP-058, month: 0)
#> 7 TTP-058 26.06962 -80.27908 11 2.3 4.5 3D (id: TTP-058, month: 0)
#> 8 TTP-058 26.06963 -80.27902 9 2.7 3.9 3D (id: TTP-058, month: 0)
#> 9 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 10 TTP-058 26.06982 -80.27900 NA 2.0 3.3 3D (id: TTP-058, month: 0)
#> geometry timestamp
#> 1 POINT EMPTY 2019-01-18 19:02:30
#> 2 POINT (-80.27906 26.06945) 2019-01-18 20:02:30
#> 3 POINT EMPTY 2019-01-18 21:02:30
#> 4 POINT EMPTY 2019-01-18 22:02:30
#> 5 POINT (-80.27431 26.06769) 2019-01-18 23:02:30
#> 6 POINT (-80.2793 26.06867) 2019-01-19 00:02:30
#> 7 POINT (-80.27908 26.06962) 2019-01-19 01:02:30
#> 8 POINT (-80.27902 26.06963) 2019-01-19 02:02:04
#> 9 POINT EMPTY 2019-01-19 03:02:30
#> 10 POINT (-80.279 26.06982) 2019-01-19 12:02:30
# convert an sftraj object to an sftime object (modified from sftrack)
if (require(sftrack)) {
# get an sftrack object
data("raccoon")
raccoon$timestamp <- as.POSIXct(raccoon$timestamp, "EST")
burstz <-
list(id = raccoon$animal_id, month = as.POSIXlt(raccoon$timestamp)$mon)
x_sftraj <-
as_sftraj(raccoon,
time = "timestamp",
error = NA, coords = c("longitude", "latitude"),
group = burstz
)
# convert to sftime
st_as_sftime(x_sftraj)
}
#> Spatiotemporal feature collection with 445 features and 8 fields (with 168 geometries empty)
#> Geometry type: GEOMETRY
#> Dimension: XY
#> Bounding box: xmin: -80.28149 ymin: 26.06761 xmax: -80.27046 ymax: 26.07706
#> CRS: NA
#> Time column with classes: 'POSIXct', 'POSIXt'.
#> Ranging from 2019-01-18 19:02:30 to 2019-02-01 18:02:30.
#> First 10 features:
#> animal_id latitude longitude height hdop vdop fix sft_group
#> 1 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 2 TTP-058 26.06945 -80.27906 7 6.2 3.2 2D (id: TTP-058, month: 0)
#> 3 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 4 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 5 TTP-058 26.06769 -80.27431 858 5.1 3.2 2D (id: TTP-058, month: 0)
#> 6 TTP-058 26.06867 -80.27930 350 1.9 3.2 3D (id: TTP-058, month: 0)
#> 7 TTP-058 26.06962 -80.27908 11 2.3 4.5 3D (id: TTP-058, month: 0)
#> 8 TTP-058 26.06963 -80.27902 9 2.7 3.9 3D (id: TTP-058, month: 0)
#> 9 TTP-058 NA NA NA 0.0 0.0 NO (id: TTP-058, month: 0)
#> 10 TTP-058 26.06982 -80.27900 NA 2.0 3.3 3D (id: TTP-058, month: 0)
#> geometry timestamp
#> 1 POINT EMPTY 2019-01-18 19:02:30
#> 2 POINT (-80.27906 26.06945) 2019-01-18 20:02:30
#> 3 POINT EMPTY 2019-01-18 21:02:30
#> 4 POINT EMPTY 2019-01-18 22:02:30
#> 5 LINESTRING (-80.27431 26.06... 2019-01-18 23:02:30
#> 6 LINESTRING (-80.2793 26.068... 2019-01-19 00:02:30
#> 7 LINESTRING (-80.27908 26.06... 2019-01-19 01:02:30
#> 8 POINT (-80.27902 26.06963) 2019-01-19 02:02:04
#> 9 POINT EMPTY 2019-01-19 03:02:30
#> 10 LINESTRING (-80.279 26.0698... 2019-01-19 12:02:30
# convert a cubble_df object from package cubble to an sftime object
if (requireNamespace("cubble", quietly = TRUE, versionCheck = "0.3.0")) {
# get a cubble_df object
data("climate_aus", package = "cubble")
# convert to sftime
climate_aus_sftime <-
st_as_sftime(climate_aus[1:4, ])
climate_aus_sftime <-
st_as_sftime(cubble::face_temporal(climate_aus)[1:4, ])
}