get_saved_par {tinyplot}

Retrieve the saved graphical parameters

Description

Convenience function for retrieving the graphical parameters (i.e., the full list of tag = value pairs held in par) from either immediately before or immediately after the most recent tinyplot call.

Usage

get_saved_par(when = c("before", "after"))

Arguments

when

character. From when should the saved parameters be retrieved? Either "before" (the default) or "after" the preceding tinyplot call.

Details

A potential side-effect of tinyplot is that it can change a user's par settings. For example, it may adjust the inner and outer plot margins to make space for an automatic legend; see draw_legend. While it is possible to immediately restore the original par settings upon exit via the tinyplot(..., restore.par = TRUE) argument, this is not the default behaviour. The reason being that we need to preserve the adjusted parameter settings in case users want to add further graphical annotations to their plot (e.g., abline, text, etc.) Nevertheless, it may still prove desirable to recall and reset these original graphical parameters after the fact (e.g., once all these extra annotations have been added). That is the purpose of this get_saved_par function.

Of course, users may prefer to manually capture and reset graphical parameters, as per the standard method described in the par documentation. For example:

op = par(no.readonly = TRUE)  # save current par settings 
# <do lots of (tiny)plotting>
par(op)                       # reset original pars

This standard manual approach may be safer than get_saved_par because it offers more precise control. Specifically, the value of get_saved_par itself will be reset after ever new tinyplot call; i.e. it may inherit an already-changed set of parameters. Users should bear these trade-offs in mind when deciding which approach to use. As a general rule, get_saved_par offers the convenience of resetting the original par settings even if a user forgot to save them beforehand. But one should avoid invoking it after a series of consecutive tinyplot calls.

Finally, note that users can always call dev.off to reset all par settings to their defaults.

Value

A list of par settings.

Examples

#
# Contrived example where we draw a grouped scatterplot with a legend and
# manually add corresponding best fit lines for each group...
#

# First draw the grouped scatterplot
tinyplot(Sepal.Length ~ Petal.Length | Species, iris)

# Preserving adjusted par settings is good for adding elements to our plot
for (s in levels(iris$Species)) {
  abline(
    lm(Sepal.Length ~ Petal.Length, iris, subset = Species==s),
    col = which(levels(iris$Species)==s)
  )
}

# Get saved par from before the preceding tinyplot call (but don't use yet)
sp = get_saved_par("before")

# Note the changed margins will affect regular plots too, which is probably
# not desirable
plot(1:10)

# Reset the original parameters (could use `par(sp)` here)
tpar(sp)
# Redraw our simple plot with our corrected right margin
plot(1:10)

#
# Quick example going the other way, "correcting" for par.restore = TRUE...
#

tinyplot(Sepal.Length ~ Petal.Length | Species, iris, restore.par = TRUE)
# Our added best lines will be wrong b/c of misaligned par
for (s in levels(iris$Species)) {
  abline(
    lm(Sepal.Length ~ Petal.Length, iris, subset = Species==s),
    col = which(levels(iris$Species)==s), lty = 2
  )
}
# grab the par settings from the _end_ of the preceding tinyplot call to fix
tpar(get_saved_par("after"))
# now the best lines are correct
for (s in levels(iris$Species)) {
  abline(
    lm(Sepal.Length ~ Petal.Length, iris, subset = Species==s),
    col = which(levels(iris$Species)==s)
  )
}

# reset again to original saved par settings before exit
tpar(sp)