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"fv".## S3 method for class 'fv':
plot(x, fmla, \dots, subset=NULL, lty=NULL, col=NULL, lwd=NULL,
xlim=NULL, ylim=NULL, xlab=NULL, ylab=NULL, ylim.covers=NULL,
legend=!add, legendpos="topleft", legendavoid=missing(legendpos),
legendmath=TRUE, legendargs=list(),
shade=fvnames(x, ".s"), shadecol="grey",
add=FALSE, log="",
mathfont=c("italic", "plain", "bold", "bolditalic"),
limitsonly=FALSE)"fv", containing the variables to be plotted
or variables from which the plotting coordinates can be computed.lty controlling the line style of each plot.col controlling the colour of each plot.lwd controlling the line width of each plot.plot.default.ylim.covers=0 will ensure that the
$y$ axis includes the origin.NULL. If legend=TRUE, the algorithm
plots a legend in the top left corner of the plot,
explaining the meaning of the different line types and colours.legend for keyword options)
or a pair of coordinates in the format list(x,y).
Alternatively if legendTRUE, the code will check for collisions between the
legend box and the graphics, and will override legendpos
if a collision occurTRUE, the legend will display the
mathematical notation for each curve. If FALSE, the legend text
is the identifier (column name) for each curve.legend controlling the appearance of the legend.x,
or another type of index that identifies two columns.
When the corresponding curves are plotted,
the region between the curves will be shaded in light grey.
The object <shade plot.
A character string or an integer specifying a colour."x" if the x axis is to
be logarithmic, "y" if the y axis is to be logarithmic and
"xy" or "yx" if both axes are to be logarithmic.FALSE, plotting is performed normally.
If TRUE, no plotting is performed at all;
just the $x$ and $y$ limits of the plot are computed
and returned.NULL, or a data frame giving the meaning of the
different line types and colours.plot method for the class "fv". The use of the argument fmla is like plot.formula, but offers
some extra functionality.
The left and right hand sides of fmla are evaluated,
and the results are plotted against each other
(the left side on the $y$ axis
against the right side on the $x$ axis).
The left and right hand sides of fmla may be
the names of columns of the data frame x,
or expressions involving these names. If a variable in fmla
is not the name of a column of x, the algorithm will search for
an object of this name in the environment where plot.fv was
called, and then in the enclosing environment, and so on.
Multiple curves may be specified by a single formula
of the form
cbind(y1,y2,...,yn) ~ x, where x,y1,y2,...,yn are
expressions involving the variables in the data frame.
Each of the variables y1,y2,...,yn in turn will be plotted
against x.
See the examples.
Convenient abbreviations which can be used in the formula are
.which represents all the
columns in the data frame that will be plotted by default;.xwhich represents the function argument;.ywhich represents the recommended value
of the function.fvnames.The value returned by this plot function indicates the meaning of the line types and colours in the plot. It can be used to make a suitable legend for the plot if you want to do this by hand. See the examples.
The argument shade can be used to display critical bands
or confidence intervals. If it is not NULL, then it should be
a subset index for the columns of x, that identifies exactly
2 columns. When the corresponding curves are plotted, the region
between the curves will be shaded in light grey. See the Examples.
The default values of lty, col and lwd can
be changed using spatstat.options("plot.fv").
Use type = "n" to create the plot region and draw the axes
without plotting any data.
Use limitsonly=TRUE to suppress all plotting
and just compute the $x$ and $y$ limits. This can be used
to calculate common $x$ and $y$ scales for several plots.
To change the kind of parenthesis enclosing the
explanatory text about the unit of length, use
spatstat.options('units.paren')
fv.object,
KestK <- Kest(cells)
# K is an object of class "fv"
plot(K, iso ~ r) # plots iso against r
plot(K, sqrt(iso/pi) ~ r) # plots sqrt(iso/r) against r
plot(K, cbind(iso,theo) ~ r) # plots iso against r AND theo against r
plot(K, . ~ r) # plots all available estimates of K against r
plot(K, sqrt(./pi) ~ r) # plots all estimates of L-function
# L(r) = sqrt(K(r)/pi)
plot(K, cbind(iso,theo) ~ r, col=c(2,3))
# plots iso against r in colour 2
# and theo against r in colour 3
plot(K, iso ~ r, subset=quote(r < 0.2))
# plots iso against r for r < 10
# Can't remember the names of the columns? No problem..
plot(K, sqrt(./pi) ~ .x)
# making a legend by hand
v <- plot(K, . ~ r, legend=FALSE)
legend("topleft", legend=v$meaning, lty=v$lty, col=v$col)
# significance bands
KE <- envelope(cells, Kest, nsim=19)
plot(KE, shade=c("hi", "lo"))
# how to display two functions on a common scale
Kr <- Kest(redwood)
a <- plot(K, limitsonly=TRUE)
b <- plot(Kr, limitsonly=TRUE)
xlim <- range(a$xlim, b$xlim)
ylim <- range(a$ylim, b$ylim)
opa <- par(mfrow=c(1,2))
plot(K, xlim=xlim, ylim=ylim)
plot(Kr, xlim=xlim, ylim=ylim)
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