as.ppp | R Documentation |
Functions to convert between spatstats planar point pattern (ppp
)
format and sps SpatialPoints
and SpatialPointsDataFrame
as
well as one-way conversion from SpatialGridDataFrame
to ppp
.
S4-style as()
coercion can be used as well.
as.ppp.SpatialPoints(X)
as.ppp.SpatialPointsDataFrame(X)
as.SpatialPoints.ppp(from)
as.SpatialPointsDataFrame.ppp(from)
as.SpatialGridDataFrame.ppp(from)
from, X |
object to coerce from |
The main conversion is between sps
SpatialPoints
/SpatialPointsDataFrame
and spatstats
ppp
. Conversion between SpatialGridDataFrame
and ppp
should
rarely be used; using as.owin.SpatialGridDataFrame
is more transparent.
signature(from = "SpatialPoints", to = "ppp")
signature(from = "SpatialPointsDataFrame", to = "ppp")
signature(from = "ppp", to = "SpatialGridDataFrame")
signature(from = "ppp", to = "SpatialPointsDataFrame")
signature(from = "ppp", to = "SpatialPoints")
In spatstat all spatial objects are assumed to be planar. This means
that spatstat is not designed to work directly with geographic
(longitude and latitude) coordinates. If a sp object is declared to
have geographic (unprojected) coordinates maptools refuses to convert
directly to spatstat format. Rather, these should be projected first
using e.g. spTransform
. If you know what you are doing, and
really want to force coercion, you can overwrite the proj4string
of the
sp object with NA
, proj4string(x) <- CRS(NA)
, which
will fool the system to think that the data is in local planar coordinates.
This is probably not a good idea!
The ppp
format requires an observation window which is the sampling
region. The sp formats contain no such information and by default the
bounding box of the points is simply used. This is almost never the correct
thing to do! Rather, information about the sampling region should be converted
into spatstats owin
format and assigned as the
observation window. Usually conversion from ppp
to sp format simply
discards the owin
. However, as.SpatialGridDataFrame.ppp
actually
first discards the points(!), second checks that the corresponding owin
is in a grid format (matrix of TRUE/FALSE for inside/outside sampling region),
and finally converts the TRUE/FALSE grid to a SpatialGridDataFrame
.
Edzer Pebesma edzer.pebesma@uni-muenster.de, Roger Bivand
run <- FALSE
if (require("spatstat.geom", quietly=TRUE)) run <- TRUE
if (run) {
## Convert SpatialPointsDataFrame into a marked ppp
data(meuse)
coordinates(meuse) = ~x+y
meuse_ppp <- as(meuse, "ppp")
meuse_ppp # Window is the bounding rectangle
}
if (run) {
plot(meuse_ppp, which.marks = "zinc")
}
if (run) {
## Convert SpatialPoints into an unmarked ppp
meuse2 <- as(meuse, "SpatialPoints")
as(meuse2, "ppp")
}
if (run) {
## Get sampling region in grid format and assign it as observation window
data(meuse.grid)
gridded(meuse.grid) <- ~x+y
mg_owin <- as(meuse.grid, "owin")
Window(meuse_ppp) <- mg_owin
meuse_ppp # Window is now a binary image mask (TRUE/FALSE grid)
}
if (run) {
plot(meuse_ppp, which.marks = "zinc")
}
if (run) {
## Convert marked ppp back to SpatialPointsDataFrame
rev_ppp_SPDF <- as.SpatialPointsDataFrame.ppp(meuse_ppp)
summary(rev_ppp_SPDF)
}
if (run) {
## Convert marked ppp back to SpatialPoints (discarding marks)
rev_ppp_SP <- as.SpatialPoints.ppp(meuse_ppp)
summary(rev_ppp_SP)
}
if (run) {
## Convert marked ppp back to SpatialGridDataFrame (extracting the window grid)
rev_ppp_SGDF <- as.SpatialGridDataFrame.ppp(meuse_ppp)
summary(rev_ppp_SGDF)
}
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