Window: Extract or Change the Window of a Spatial Object

Description

Given a spatial object (such as a point pattern or pixel image) in two dimensions, these functions extract or change the window in which the object is defined.

Usage

Window(X, ...)
   Window(X, ...) <- value
   # S3 method for ppp
Window(X, ...)
   # S3 method for ppp
Window(X, ...) <- value
   # S3 method for quad
Window(X, ...)
   # S3 method for quad
Window(X, ...) <- value
   # S3 method for psp
Window(X, ...)
   # S3 method for psp
Window(X, ...) <- value
   # S3 method for im
Window(X, ...)
   # S3 method for im
Window(X, ...) <- value

Value

The result of Window is a window (object of class

"owin").

The result of Window<- is the updated object X, of the same class as X.

Arguments

X: A spatial object such as a point pattern, line segment pattern or pixel image.
...: Extra arguments. They are ignored by all the methods listed here.
value: Another window (object of class "owin") to be used as the window for X.

Author

Adrian Baddeley Adrian.Baddeley@curtin.edu.au, Rolf Turner r.turner@auckland.ac.nz and Ege Rubak rubak@math.aau.dk.

Details

The functions Window and Window<- are generic.

Window(X) extracts the spatial window in which X is defined.

Window(X) <- W changes the window in which X is defined to the new window W, and discards any data outside W. In particular:

If X is a point pattern (object of class "ppp") then Window(X) <- W discards any points of X which fall outside W.
If X is a quadrature scheme (object of class "quad") then Window(X) <- W discards any points of X which fall outside W, and discards the corresponding quadrature weights.
If X is a line segment pattern (object of class "psp") then Window(X) <- W clips the segments of X to the boundaries of W.
If X is a pixel image (object of class "im") then Window(X) <- W has the effect that pixels lying outside W are retained but their pixel values are set to NA.

Many other classes of spatial object have a method for Window, but not Window<-. See Window.tess.

Examples

Run this code

   ## point patterns
   Window(cells)
   X <- demopat
   Window(X)
   Window(X) <- as.rectangle(Window(X))

   ## line segment patterns
   X <- psp(runif(10), runif(10), runif(10), runif(10), window=owin())
   Window(X)
   Window(X) <- square(0.5)

   ## images
   Z <- setcov(owin())
   Window(Z)
   Window(Z) <- square(0.5)

Run the code above in your browser using DataLab

Data engineering and BI courses are free!