| RLlegend {Renext} | R Documentation |
Legend management for return level plots
Description
Legend management for return level plots produced with the plot
and lines method of the "Renouv" class.
Usage
RLlegend.ini(x = "topleft", bty = "n", ...)
RLlegend.show()
Arguments
x |
A possible value for the |
bty |
As in |
... |
Other arguments to be kept in the list and passed later to
|
Details
This function is to be used in conjunction with
plot.Renouv and lines.Renouv methods. It
allows the construction of a legend in a semi-automatic fashion, using
the value of the par argument of the plot and
lines methods to specify the legend construction.
Each call to the plot.Renouv or
lines.Renouv changes the content of a list variable
named .RLlegend in a special environment bound to the
package. This list is re-created when RLlegend.ini is called,
and is used later to draw a legend on the active device when
RLlegend.show is called. Between these two calls, the
plot and lines methods should be used with their arg
legend set to FALSE.
Value
RLlegend.ini returns a copy of the variable which is set.
RLlegend.show returns nothing.
Note
The size of symbols (i.e, plotting characters) can be set by
using the RLpar function and the par
argument of the methods plot.Renouv and
lines.Renouv. However it can not be changed in the
legend.
Author(s)
Yves Deville
See Also
plot.Renouv and lines.Renouv for
and the RLpar function to change the graphical
parameters of the plot and the legend by using the par
argument.
Examples
## use Garonne data
xG <- Garonne$OTdata$Flow
## use special "exponential" distribution
fit1 <- Renouv(x = xG, threshold = 2500, distname.y = "exponential",
effDuration = 65, plot = FALSE)
## use 'exp' in black box fashion, hence with delta method
fit2 <- Renouv(x = xG, , threshold = 2500, distname.y = "exp",
effDuration = 65, start.par.y = c(rate = 1), plot = FALSE)
RLlegend.ini() ## initialise legend
## sample points only
plot(fit1, main = "Two types of confidence lims",
show = list(OT = TRUE, quant = FALSE, conf = FALSE),
label = "",
legend = FALSE)
## quant and confidence lims
lines(fit1,
show = list(OT = FALSE, quant = TRUE, conf = TRUE),
label = "exact",
legend = FALSE)
## quant (overplot) and confidence lims
lines(fit2,
show = list(OT = FALSE, quant = TRUE, conf = TRUE),
par = RLpar(quant.lty = 2, quant.col = "SpringGreen2",
conf.conf1.col = "orangered", conf.conf1.lwd = 3,
conf.conf2.col = "orangered", conf.conf2.lwd = 3),
label = "delta",
legend = FALSE)
RLlegend.show() ## now draw legend