Converts a point pattern to a pixel image. The value in each pixel is the number of points falling in that pixel, and is typically either 0 or 1.
# S3 method for ppp
pixellate(x, W=NULL, …, weights = NULL,
padzero=FALSE, fractional=FALSE, preserve=FALSE,
DivideByPixelArea=FALSE, savemap=FALSE)# S3 method for ppp
as.im(X, …)
Point pattern (object of class "ppp").
Arguments passed to as.mask to determine
the pixel resolution
Optional window mask (object of class "owin") determining
the pixel raster.
Optional vector of weights associated with the points.
Logical value indicating whether to set pixel values to zero outside the window.
Logical values determining the type of discretisation. See Details.
Logical value, indicating whether the resulting pixel values should be divided by the pixel area.
Logical value, indicating whether to save information
about the discretised coordinates of the points of x.
A pixel image (object of class "im").
The functions pixellate.ppp and as.im.ppp
convert a spatial point pattern x into a pixel
image, by counting the number of points (or the total weight of
points) falling in each pixel.
Calling as.im.ppp is equivalent to
calling pixellate.ppp with its default arguments.
Note that pixellate.ppp is more general than as.im.ppp
(it has additional arguments for greater flexibility).
The functions as.im.ppp and pixellate.ppp
are methods for the generic functions as.im
and pixellate respectively,
for the class of point patterns.
The pixel raster (in which points are counted) is determined
by the argument W if it is present (for pixellate.ppp only).
In this case W should be a binary mask (a window object of
class "owin" with type "mask").
Otherwise the pixel raster is determined by
extracting the window containing x and converting it to a
binary pixel mask using as.mask. The arguments
… are passed to as.mask to
control the pixel resolution.
If weights is NULL, then for each pixel
in the mask, the algorithm counts how many points in x fall
in the pixel. This count is usually either 0 (for a pixel with no data
points in it) or 1 (for a pixel containing one data point) but may be
greater than 1. The result is an image with these counts as its pixel values.
If weights is given, it should be a numeric vector of the same
length as the number of points in x. For each pixel, the
algorithm finds the total weight associated with points in x that fall
in the given pixel. The result is an image with these total weights
as its pixel values.
By default (if zeropad=FALSE) the resulting pixel image has the same
spatial domain as the window of the point pattern x. If
zeropad=TRUE then the resulting pixel image has a rectangular
domain; pixels outside the original window are assigned the value zero.
The discretisation procedure is controlled by the arguments
fractional and preserve.
The argument fractional specifies how data points are mapped to
pixels. If fractional=FALSE (the default),
each data point is allocated to the nearest pixel centre.
If fractional=TRUE, each data point is allocated
with fractional weight to four pixel centres
(the corners of a rectangle containing the data
point).
The argument preserve specifies what to do with pixels
lying near the boundary of the window, if the window is not a rectangle.
If preserve=FALSE (the default), any contributions
that are attributed to pixel centres lying outside the window
are reset to zero. If preserve=TRUE, any such contributions
are shifted to the nearest pixel lying inside the window, so that
the total mass is preserved.
If savemap=TRUE then the result has an attribute
"map" which is a 2-column matrix containing the row and column
indices of the discretised positions of the points of x
in the pixel grid.
# NOT RUN {
plot(pixellate(humberside))
plot(pixellate(humberside, fractional=TRUE))
# }
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