# as.owin

0th

Percentile

##### Convert Data To Class owin

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

Keywords
manip, spatial
##### 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 flag 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.

##### Details

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

This function 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 four-element vector (interpreted as (xmin, xmax, ymin, ymax)) specifying the $x$ and $y$ dimensions of a rectangle

• a structure with entries xl, xu, yl, yu 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 library.

• 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.

##### Value

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

owin.object, owin

##### Aliases
• as.owin
• as.owin.owin
• as.owin.ppp
• as.owin.ppm
• as.owin.kppm
• as.owin.dppm
• as.owin.lpp
• as.owin.lppm
• as.owin.msr
• as.owin.psp
• as.owin.tess
• as.owin.im
• as.owin.layered
• as.owin.data.frame
• as.owin.distfun
• as.owin.nnfun
• as.owin.funxy
• as.owin.boxx
• as.owin.rmhmodel
• as.owin.leverage.ppm
• as.owin.influence.ppm
• as.owin.default
##### Examples
# 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)
# }

Documentation reproduced from package spatstat, version 1.52-1, License: GPL (>= 2)

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