spatstat (version 1.55-1)

as.owin: Convert Data To Class owin

Description

Converts data specifying an observation window in any of several formats, into an object of class "owin".

Usage

as.owin(W, …, fatal=TRUE)

# S3 method for owin as.owin(W, …, fatal=TRUE)

# S3 method for ppp as.owin(W, …, fatal=TRUE)

# S3 method for ppm as.owin(W, …, from=c("points", "covariates"), fatal=TRUE)

# S3 method for kppm as.owin(W, …, from=c("points", "covariates"), fatal=TRUE)

# S3 method for dppm as.owin(W, …, from=c("points", "covariates"), fatal=TRUE)

# S3 method for lpp as.owin(W, …, fatal=TRUE)

# S3 method for lppm as.owin(W, …, fatal=TRUE)

# S3 method for msr as.owin(W, …, fatal=TRUE)

# S3 method for psp as.owin(W, …, fatal=TRUE)

# S3 method for quad as.owin(W, …, fatal=TRUE)

# S3 method for quadratcount as.owin(W, …, fatal=TRUE)

# S3 method for quadrattest as.owin(W, …, fatal=TRUE)

# S3 method for tess as.owin(W, …, fatal=TRUE)

# S3 method for im as.owin(W, …, fatal=TRUE)

# S3 method for layered as.owin(W, …, fatal=TRUE)

# S3 method for data.frame as.owin(W, …, step, fatal=TRUE)

# S3 method for distfun as.owin(W, …, fatal=TRUE)

# S3 method for nnfun as.owin(W, …, fatal=TRUE)

# S3 method for funxy as.owin(W, …, fatal=TRUE)

# S3 method for boxx as.owin(W, …, fatal=TRUE)

# S3 method for rmhmodel as.owin(W, …, fatal=FALSE)

# S3 method for leverage.ppm as.owin(W, …, fatal=TRUE)

# S3 method for influence.ppm as.owin(W, …, fatal=TRUE)

# S3 method for default as.owin(W, …, fatal=TRUE)

Arguments

W

Data specifying an observation window, in any of several formats described under Details below.

fatal

Logical value determining what to do if the data cannot be converted to an observation window. See Details.

Ignored.

from

Character string. See Details.

step

Optional. A single number, or numeric vector of length 2, giving the grid step lengths in the \(x\) and \(y\) directions.

Value

An object of class "owin" (see owin.object) specifying an observation window.

Details

The class "owin" is a way of specifying the observation window for a point pattern. See owin.object for an overview.

The function as.owin converts data in any of several formats into an object of class "owin" for use by the spatstat package. The function as.owin is generic, with methods for different classes of objects, and a default method.

The argument W may be

  • an object of class "owin"

  • a structure with entries xrange, yrange specifying the \(x\) and \(y\) dimensions of a rectangle

  • a structure with entries named xmin, xmax, ymin, ymax (in any order) specifying the \(x\) and \(y\) dimensions of a rectangle. This will accept objects of class bbox in the sf package.

  • a numeric vector of length 4 (interpreted as (xmin, xmax, ymin, ymax) in that order) specifying the \(x\) and \(y\) dimensions of a rectangle

  • a structure with entries named xl, xu, yl, yu (in any order) specifying the \(x\) and \(y\) dimensions of a rectangle as (xmin, xmax) = (xl, xu) and (ymin, ymax) = (yl, yu). This will accept objects of class spp used in the Venables and Ripley spatial package.

  • an object of class "ppp" representing a point pattern. In this case, the object's window structure will be extracted.

  • an object of class "psp" representing a line segment pattern. In this case, the object's window structure will be extracted.

  • an object of class "tess" representing a tessellation. In this case, the object's window structure will be extracted.

  • an object of class "quad" representing a quadrature scheme. In this case, the window of the data component will be extracted.

  • an object of class "im" representing a pixel image. In this case, a window of type "mask" will be returned, with the same pixel raster coordinates as the image. An image pixel value of NA, signifying that the pixel lies outside the window, is transformed into the logical value FALSE, which is the corresponding convention for window masks.

  • an object of class "ppm", "kppm" or "dppm" representing a fitted point process model. In this case, if from="data" (the default), as.owin extracts the original point pattern data to which the model was fitted, and returns the observation window of this point pattern. If from="covariates" then as.owin extracts the covariate images to which the model was fitted, and returns a binary mask window that specifies the pixel locations.

  • an object of class "lpp" representing a point pattern on a linear network. In this case, as.owin extracts the linear network and returns a window containing this network.

  • an object of class "lppm" representing a fitted point process model on a linear network. In this case, as.owin extracts the linear network and returns a window containing this network.

  • A data.frame with exactly three columns. Each row of the data frame corresponds to one pixel. Each row contains the \(x\) and \(y\) coordinates of a pixel, and a logical value indicating whether the pixel lies inside the window.

  • A data.frame with exactly two columns. Each row of the data frame contains the \(x\) and \(y\) coordinates of a pixel that lies inside the window.

  • an object of class "distfun", "nnfun" or "funxy" representing a function of spatial location, defined on a spatial domain. The spatial domain of the function will be extracted.

  • an object of class "rmhmodel" representing a point process model that can be simulated using rmh. The window (spatial domain) of the model will be extracted. The window may be NULL in some circumstances (indicating that the simulation window has not yet been determined). This is not treated as an error, because the argument fatal defaults to FALSE for this method.

  • an object of class "layered" representing a list of spatial objects. See layered. In this case, as.owin will be applied to each of the objects in the list, and the union of these windows will be returned.

If the argument W is not in one of these formats and cannot be converted to a window, then an error will be generated (if fatal=TRUE) or a value of NULL will be returned (if fatal=FALSE).

When W is a data frame, the argument step can be used to specify the pixel grid spacing; otherwise, the spacing will be guessed from the data.

See Also

owin.object, owin

Examples

Run this code
# NOT RUN {
 w <- as.owin(c(0,1,0,1))
 w <- as.owin(list(xrange=c(0,5),yrange=c(0,10)))
 # point pattern
 data(demopat)
 w <- as.owin(demopat)
 # image
 Z <- as.im(function(x,y) { x + 3}, unit.square())
 w <- as.owin(Z)

 # Venables & Ripley 'spatial' package
 require(spatial)
 towns <- ppinit("towns.dat")
 w <- as.owin(towns)
 detach(package:spatial)
# }

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