foodweb is applied to a group of functions (e.g. all those in a workspace); it produces a graphical display showing the hierarchy of which functions call which other ones. This is handy, for instance, when you have a great morass of functions in a workspace, and want to figure out which ones are meant to be called directly. callers.of(funs) and callees.of(funs) show which functions directly call, or are called directly by, funs.foodweb( funs, where=1, charlim=80, prune=character(0), rprune, ancestors=TRUE,
descendents=TRUE, plotting =TRUE, plotmath=FALSE,
generics=c( "c","print","plot", "["), lwd=0.5, xblank=0.18,
border="transparent", boxcolor="white", textcolor="black",
color.lines=TRUE, highlight="red", ...)
plot.foodweb(x, textcolor, boxcolor, xblank, border, textargs = list(),
use.centres = TRUE, color.lines = TRUE, poly.args = list(),
expand.xbox = 1.05, expand.ybox = expand.xbox * 1.2, plotmath = FALSE, ...)
callers.of( funs, fw=foodweb( plotting=FALSE))
callees.of( funs, fw=foodweb( plotting=FALSE))foodweb only) the result of a previous foodweb callfuns will be shown; otherwise, only ancestors and descendants of functions in prune will be shown. Augments funs if required.prune; prune <- funs %matching% rprune. Does NOT augment funs. Overrides prune if set.prune functions?prune functions?generics won't be shownparTRUE/FALSE)plot.foodweb and thence to parTRUE is more accurate but less tidy with big webs.rect when boxes are drawnfoodweb, or the funmat element thereof (see VALUE)plot.foodweb)foodweb returns an object of (S3) class foodweb. This has three components:dimnames are the function names.par("usr") unitspar("usr") units. For small numbers of functions, this will be an integer; for larger numbers, there will some adjustment around the nearest integerfunmat, which can be used to work out the "pecking order" and e.g. which functions directly call a given function.
callers.of and callees.of return a character vector of function names.foodweb makes some effort to arrange the functions on the display to keep the number of crossing lines low, but this is a hard problem! Judicious use of prune will help keep the display manageable. Perhaps counterintuitively, any functions NOT linked to those in prune (which all will be, by default) will be pruned from the display.
foodweb tries to catch names of functions that are stored as text, and it will pick up e.g. glm in "do.call( glm, glm.args)". There are limits to this, of course (?methods?).
The argument list may be somewhat daunting, but the only ones normally used are funs, where, and prune. Also, to get a readable display, you may need to reduce cex and/or charlim. A number of the less-obvious arguments are set by other functions which rely on plot.foodweb to do their display work. Several may disappear in future versions.
If the display from foodweb is unclear, try foodweb( .Last.value, cex=<>, charlim=<>) . This works because foodweb will also accept a foodweb-class object as its argument. You can also assign the result of foodweb to a variable, which is useful if you expect to do a lot of tinkering with the display, or to inspect the who-calls-whom matrix by hand.
callers.of and callees.of process the output of foodweb, looking for immediate dependencies only. The second argument will call foodweb by default, so it may be more efficient to call foodweb first and assign the result to a variable.foodweb( ) # functions in .GlobalEnv
foodweb( where="package:mvbutils", cex=0.4, charlim=60) # yikes!
foodweb( c( find.funs("package:mvbutils"), "paste"))
# functions in .GlobalEnv, and "paste"
foodweb( find.funs("package:mvbutils"), prune="paste")
# only those parts of the tree connected to "paste";
# NB that funs <- unique( c( funs, prune)) inside "foodweb"
foodweb( where='package:mvbutils', rprune="aste")
# doesn't include "paste" as it's not in "mvbutils", and rprune doesn't augment funs
foodweb( where='package:mvbutils', rprune="name") # does work
fw <- foodweb( where="package:mvbutils")
fw$funmat # a big matrix
callers.of( "mlocal", fw)
callees.of( find.funs() %matching% "name", fw)Run the code above in your browser using DataLab