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Plot a two-dimensional spatial point pattern
# S3 method for ppp
plot(x, main, …, clipwin=NULL,
chars=NULL, cols=NULL,
use.marks=TRUE, which.marks=NULL,
add=FALSE, type=c("p","n"),
legend=TRUE,
leg.side=c("left", "bottom", "top", "right"),
leg.args=list(),
symap=NULL, maxsize=NULL, meansize=NULL, markscale=NULL,
zap=0.01,
show.window=show.all, show.all=!add, do.plot=TRUE,
multiplot=TRUE)The spatial point pattern to be plotted.
An object of class "ppp",
or data which can be converted into
this format by as.ppp().
text to be displayed as a title above the plot.
extra arguments that will be passed to the plotting functions
plot.default, points and/or
symbols.
Optional. A window (object of class "owin").
Only this subset of the image will be displayed.
plotting character(s) used to plot points.
the colour(s) used to plot points.
logical flag; if TRUE, plot points using a different
plotting symbol for each mark;
if FALSE, only the locations of the points will be plotted,
using points().
Index determining which column of marks to use,
if the marks of x are a data frame.
A character or integer vector identifying one or more
columns of marks.
If add=FALSE then
the default is to plot all columns of marks, in a series of separate
plots.
If add=TRUE then only one column of marks can be plotted,
and the default is which.marks=1
indicating the first column of marks.
logical flag; if TRUE,
just the points are plotted, over the existing plot.
A new plot is not created, and
the window is not plotted.
Type of plot: either "p" or "n".
If type="p" (the default), both the points and the observation window
are plotted. If type="n", only the window is plotted.
Logical value indicating whether to add a legend showing the mapping between mark values and graphical symbols (for a marked point pattern).
Position of legend relative to main plot.
List of additional arguments passed to plot.symbolmap
or symbolmap to control the legend.
In addition to arguments documented under
plot.symbolmap, and graphical arguments recognised
by symbolmap, the list may also include the argument
sep giving the separation between the main plot and the
legend, or sep.frac giving the separation as a fraction
of the relevant dimension (width or height) of the main plot.
Optional. The graphical symbol map to be applied to the marks.
An object of class "symbolmap"; see
symbolmap.
Maximum physical size of the circles/squares plotted
when x is a marked point pattern with
numerical marks.
Incompatible with meansize and markscale.
Ignored if symap is given.
Average physical size of the circles/squares plotted
when x is a marked point pattern with
numerical marks.
Incompatible with maxsize and markscale.
Ignored if symap is given.
physical scale factor determining the sizes of the
circles/squares plotted when x is a marked point pattern with
numerical marks. Mark value will be multiplied by markscale
to determine physical size.
Incompatible with maxsize and meansize.
Ignored if symap is given.
Fraction between 0 and 1.
When x is a marked point pattern with numerical marks,
zap is the smallest mark value
(expressed as a fraction of the maximum possible mark) that will
be plotted.
Any points which have marks smaller in absolute value
than zap * max(abs(marks(x))) will not be plotted.
Logical value indicating whether to plot the observation
window of x.
Logical value indicating whether to plot everything
including the main title and the observation window of x.
Logical value determining whether to actually perform the plotting.
Logical value giving permission to display multiple plots.
(Invisible) object of class "symbolmap"
giving the correspondence between
mark values and plotting characters.
A frequently-asked question is: How do I remove the white space around
the plot? Currently plot.ppp uses the base graphics system of
R, so the space around the plot is controlled by parameters
to par. To reduce the white space, change the
parameter mar. Typically, par(mar=rep(0.5, 4)) is
adequate, if there are no annotations or titles outside the window.
This is the plot method for
point pattern datasets (of class "ppp", see ppp.object).
First the observation window Window(x) is plotted
(if show.window=TRUE).
Then the points themselves are plotted,
in a fashion that depends on their marks,
as follows.
If the point pattern does not have marks, or if use.marks = FALSE,
then the locations of all points will be plotted
using a single plot character
If x$marks is a factor, then
each level of the factor is
represented by a different plot character.
If x$marks is a numeric vector,
the marks are rescaled to the unit interval and
each point is represented by a circle
with diameter proportional to the rescaled mark
(if the value is positive) or a square with side length
proportional to the absolute value of the rescaled mark
(if the value is negative).
If x$marks is neither numeric nor a factor,
then each possible mark will be represented by a
different plotting character. The default is to
represent the points(..., pch=i).
If there are several columns of marks, and if which.marks is
missing or NULL, then
if add=FALSE and multiplot=TRUE
the default is to plot all columns of marks, in a series of separate
plots, placed side-by-side. The plotting is coordinated by
plot.listof, which calls plot.ppp to make each of
the individual plots.
Otherwise, only one column of marks can be plotted,
and the default is which.marks=1
indicating the first column of marks.
Plotting of the window Window(x) is performed by
plot.owin. This plot may be modified
through the ... arguments. In particular the
extra argument border determines
the colour of the window, if the window is not a binary mask.
Plotting of the points themselves is performed
by the function points, except for the case of
continuous marks, where it is performed by symbols.
Their plotting behaviour may be modified through the ...
arguments.
The argument chars determines the plotting character
or characters used to display the points (in all cases except
for the case of continuous marks). For an unmarked point pattern,
this should be a single integer or character determining a
plotting character (see par("pch")).
For a multitype point pattern, chars should be a vector
of integers or characters, of the same length
as levels(x$marks), and then the chars[i].
If chars is absent, but there is an extra argument
pch, then this will determine the plotting character for
all points.
The argument cols determines the colour or colours used to
display the points. For an unmarked point pattern,
cols should be a character string
determining a colour. For a multitype point pattern, cols
should be a character vector, of the same length
as levels(marks(x)): that is, there is one colour for each
possible mark value. The cols[i]. For a point pattern with
continuous marks, cols can be either a character string
or a character vector specifying colour values: the range of mark
values will be mapped to the specified colours.
If cols is absent, the colours used to plot the
points may be determined by the extra argument fg
(for multitype point patterns) or the extra argument col
(for all other cases). Note that specifying col will also
apply this colour to the window itself.
The default colour for the points is a semi-transparent grey,
if this is supported by the plot device. This behaviour can be
suppressed (so that the default colour is non-transparent)
by setting spatstat.options(transparent=FALSE).
The arguments maxsize, meansize and markscale
incompatible. They control the physical size of the circles and
squares which represent the marks in a point pattern with continuous
marks. The size of a circle is defined as its diameter;
the size of a square is its side length.
If markscale is given, then a mark value of m
is plotted as a circle of diameter m * markscale
(if m is positive) or a square of side abs(m) * markscale
(if m is negative). If maxsize is given, then the
largest mark in absolute value, mmax=max(abs(marks(x))),
will be scaled to have physical size maxsize.
If meansize is given, then the
average absolute mark value, mmean=mean(abs(marks(x))),
will be scaled to have physical size meansize.
The user can set the default values of these plotting parameters
using spatstat.options("par.points").
To zoom in (to view only a subset of the point pattern at higher
magnification), use the graphical arguments
xlim and ylim to specify the rectangular field of view.
The value returned by this plot function is an object of
class "symbolmap" representing the mapping from mark values
to graphical symbols. See symbolmap.
It can be used to make a suitable legend,
or to ensure that two plots use the same graphics map.
# NOT RUN {
plot(cells)
plot(cells, pch=16)
# make the plotting symbols larger (for publication at reduced scale)
plot(cells, cex=2)
# set it in spatstat.options
oldopt <- spatstat.options(par.points=list(cex=2))
plot(cells)
spatstat.options(oldopt)
# multitype
plot(lansing)
# marked by a real number
plot(longleaf)
# just plot the points
plot(longleaf, use.marks=FALSE)
plot(unmark(longleaf)) # equivalent
# point pattern with multiple marks
plot(finpines)
plot(finpines, which.marks="height")
# controlling COLOURS of points
plot(cells, cols="blue")
plot(lansing, cols=c("black", "yellow", "green",
"blue","red","pink"))
plot(longleaf, fg="blue")
# make window purple
plot(lansing, border="purple")
# make everything purple
plot(lansing, border="purple", cols="purple", col.main="purple",
leg.args=list(col.axis="purple"))
# controlling PLOT CHARACTERS for multitype pattern
plot(lansing, chars = 11:16)
plot(lansing, chars = c("o","h","m",".","o","o"))
## multitype pattern mapped to symbols
plot(amacrine, shape=c("circles", "squares"), size=0.04)
plot(amacrine, shape="arrows", direction=c(0,90), size=0.07)
## plot trees as trees!
plot(lansing, shape="arrows", direction=90, cols=1:6)
# controlling MARK SCALE for pattern with numeric marks
plot(longleaf, markscale=0.1)
plot(longleaf, maxsize=5)
plot(longleaf, meansize=2)
# draw circles of diameter equal to nearest neighbour distance
plot(cells %mark% nndist(cells), markscale=1, legend=FALSE)
# inspecting the symbol map
v <- plot(amacrine)
v
## variable colours ('cols' not 'col')
plot(longleaf, cols=function(x) ifelse(x < 30, "red", "black"))
## re-using the same mark scale
a <- plot(longleaf)
juveniles <- longleaf[marks(longleaf) < 30]
plot(juveniles, symap=a)
## numerical marks mapped to symbols of fixed size with variable colour
ra <- range(marks(longleaf))
colmap <- colourmap(terrain.colors(20), range=ra)
## filled plot characters are the codes 21-25
## fill colour is indicated by 'bg'
sy <- symbolmap(pch=21, bg=colmap, range=ra)
plot(longleaf, symap=sy)
## or more compactly..
plot(longleaf, bg=terrain.colors(20), pch=21, cex=1)
## clipping
plot(humberside)
B <- owin(c(4810, 5190), c(4180, 4430))
plot(B, add=TRUE, border="red")
plot(humberside, clipwin=B, main="Humberside (clipped)")
# }
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