Plot Pixel Image on Linear Network
Given a pixel image on a linear network, the pixel values are displayed either as colours or as line widths.
## S3 method for class 'linim' plot(x, ..., style = c("colour", "width"), scale, adjust = 1, fatten = 0, negative.args = list(col=2), legend=TRUE, leg.side=c("right", "left", "bottom", "top"), leg.sep=0.1, leg.wid=0.1, leg.args=list(), leg.scale=1, zlim, box=FALSE, do.plot=TRUE)
x |
The pixel image to be plotted. An object of class |
... |
Extra graphical parameters, passed to |
style |
Character string (partially matched) specifying the type of plot. See Details. |
scale |
Physical scale factor for representing the pixel values as line widths. |
adjust |
Adjustment factor for the conversion of
pixel value to line width, when |
fatten |
Distance by which the line segments should be thickened,
when |
negative.args |
A list of arguments to be passed to |
legend |
Logical value indicating whether to plot a legend (colour ribbon or scale bar). |
leg.side |
Character string (partially matched) indicating where to display the legend relative to the main image. |
leg.sep |
Factor controlling the space between the legend and the image. |
leg.wid |
Factor controlling the width of the legend. |
leg.scale |
Rescaling factor for annotations on the legend. The values on the numerical scale printed beside the legend will be multiplied by this rescaling factor. |
leg.args |
List of additional arguments passed to
|
zlim |
The range of numerical values that should be mapped.
A numeric vector of length 2.
Defaults to the range of values of |
box |
Logical value indicating whether to draw a bounding box. |
do.plot |
Logical value indicating whether to actually perform the plot. |
This is the plot
method for objects
of class "linim"
. Such an object represents
a pixel image defined on a linear network.
If style="width"
then
the pixel values of x
are used to determine the widths of
thick lines centred on the line segments of the linear network.
The mapping from pixel values to line widths is determined by
the arguments scale
and adjust
.
The plotting of colours and borders of the lines is controlled by
the additional arguments ...
which are passed to
polygon
. A different set of colours and borders can be
assigned to negative pixel values by passing a list of arguments in
negative.args
as shown in the Examples.
A legend is displayed alongside the plot
if legend=TRUE
(the default). The legend
displays the relationship between pixel values and colours
(if style="colour"
) or between pixel values and
line widths (if style="width"
).
The plotting of the legend itself is controlled by the arguments
leg.side
, leg.sep
, leg.wid
, leg.scale
and the list of arguments leg.args
, which are described above.
If style="colour"
, these arguments are mapped to
the arguments ribside
, ribsep
, ribwid
,
ribscale
and ribargs
respectively, which are passed
to plot.im
.
If style="colour"
, the result is
an object of class "colourmap"
specifying the colour map used.
If style="width"
, the result is
a numeric value v
giving the physical scale:
one unit of pixel value is represented as v
physical units on the plot.
The result also has an attribute "bbox"
giving a bounding box
for the plot. The bounding box includes the ribbon or scale bar, if present,
but not the main title.
When style="colour"
it often appears that the lines are
drawn too thin. This occurs because x
is a pixel image,
in which the only pixels that have a defined value are those which lie
directly over the network. To make the lines appear thicker in the
plot, use the argument fatten
. The domain of the image will be
expanded by a distance equal to fatten/2
in every direction
using dilation.owin
; the pixel values will
be extrapolated to this expanded domain using
nearestValue
. This may improve the visual appearance
of the plot.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au
Ang, Q.W., Baddeley, A. and Nair, G. (2012) Geometrically corrected second-order analysis of events on a linear network, with applications to ecology and criminology. Scandinavian Journal of Statistics 39, 591–617.
X <- linfun(function(x,y,seg,tp){y^2+x}, simplenet) X <- as.linim(X) plot(X, main="Colour represents function value") plot(X, fatten=0.02, main="fattened") plot(X, style="width", main="Width proportional to function value") # signed values f <- linfun(function(x,y,seg,tp){y-x}, simplenet) plot(f, style="w", main="Negative values in red") plot(f, style="w", negative.args=list(density=10), main="Negative values are hatched")
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