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"owin" representing
an observation window in the two-dimensional planeowin()
owin(xrange, yrange)
owin(poly=xy)
owin(xrange, yrange, poly=xy)
owin(xrange, yrange, mask=mat)
owin(mask=mat)"owin"
describing a window in the two-dimensional plane.spatstat library, a point pattern dataset must include
information about the window of observation. This is represented by
an object of class "owin".
See owin.object for an overview. To create a window in its own right,
users would normally invoke owin,
although sometimes as.owin may be convenient.
A window may be rectangular, polygonal, or a mask (a binary image).
xrangeandyrangeare given, then
the window will be rectangular, with its$x$and$y$coordinate dimensions given by these two arguments
(which must be vectors of length 2).
If no arguments are given at all, the default is the unit square
with dimensionsxrange=c(0,1)andyrange=c(0,1).polyis given, then the window will be polygonal.polyis a structure with
two component vectorsxandyof equal length,
then these vectors are interpreted as the cartesian coordinates
of the vertices of a polygon circumscribing the window.
The vertices must be listedanticlockwise.
No vertex should be repeated (i.e. do not repeat the first
vertex).polyis a list, each entrypoly[[i]]of which is a structure with
two component vectorsxandyof equal length,
then the successive list memberspoly[[i]]are interpreted as separate polygons which together
make up the boundary of the window.
The vertices of each polygon must be listedanticlockwiseif the polygon is part of the external boundary,
butclockwiseif the polygon is the boundary of a hole in the window.
Again, do not repeat any vertex.maskis given, then the window will be a binary image.
The argumentmaskshould be a logical matrix
such thatmask[i,j]isTRUEif the point(x[j],y[i])belongs to the window, andFALSEif it
does not. Note carefully that rows ofmaskcorrespond to the$y$coordinate, and columns to the$x$coordinate.
Herexandyare vectors of$x$and$y$coordinates equally spaced overxrangeandyrangerespectively.raster.x() and raster.y()
as in the examples below.owin.object,
as.owin,
complement.owin,
ppp.object,
pppw <- owin()
w <- owin(c(0,1), c(0,1))
# the unit square
w <- owin(c(10,20), c(10,30))
# a rectangle of dimensions 10 x 20 units
# with lower left corner at (10,10)
# polygon (diamond shape)
w <- owin(poly=list(x=c(0.5,1,0.5,0),y=c(0,1,2,1)))
w <- owin(c(0,1), c(0,2), poly=list(x=c(0.5,1,0.5,0),y=c(0,1,2,1)))
# polygon with hole
ho <- owin(poly=list(list(x=c(0,1,1,0), y=c(0,0,1,1)),
list(x=c(0.6,0.4,0.4,0.6), y=c(0.2,0.2,0.4,0.4))))
w <- owin(c(-1,1), c(-1,1), mask=matrix(TRUE, 100,100))
# 100 x 100 image, all TRUE
X <- raster.x(w)
Y <- raster.y(w)
wm <- owin(w$xrange, w$yrange, mask=(X^2 + Y^2 <= 1))
# discrete approximation to the unit disc
plot(c(0,1),c(0,1),type="n")
bdry <- locator()
# click the vertices of a polygon (anticlockwise)
<testonly>bdry <- list(x=c(0.1,0.3,0.7,0.4,0.2),
y=c(0.1,0.1,0.5,0.7,0.3))</testonly>
w <- owin(poly=bdry)
plot(w)
im <- as.logical(matrix(scan("myfile"), nrow=128, ncol=128))
# read in an arbitrary 128 x 128 digital image from text file
rim <- im[, 128:1]
# Assuming it was given in row-major order in the file
# i.e. scanning left-to-right in rows from top-to-bottom,
# the use of matrix() has effectively transposed rows & columns,
# so to convert it to our format just reverse the column order.
w <- owin(mask=rim)
plot(w)
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