# NOT RUN {
  w <- owin()
  w <- owin(c(0,1), c(0,1))
  # the unit square
  w <- owin(c(10,20), c(10,30), unitname=c("foot","feet"))
  # a rectangle of dimensions 10 x 20 feet
  # 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
  # vertices of a polygon (listed anticlockwise)
  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))
  # vertices could alternatively be read from a file, or use locator()
  w <- owin(poly=bdry)
 
 
# }
# NOT RUN {
 # how to read in a binary mask from a file
 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)
 # display it to check!
 
# }
Run the code above in your browser using DataLab