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

.

`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)

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.

An object of class `"owin"`

(see `owin.object`

)
specifying an observation window.

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 rectanglea four-element vector (interpreted as

`(xmin, xmax, ymin, ymax)`

) specifying the \(x\) and \(y\) dimensions of a rectanglea 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.

```
# 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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