gsubfn (version 0.3-1)

fn: Transform formula arguments to functions.

Description

When used in the form fn$somefunction(...arguments...) it converts formulas among the arguments of somefunction to functions using as.function.formula. It uses a heuristic to decide which formulas to convert. If any of the following are true then that argument is converted from a formula to a function: (1) there is only one formula among the arguments, (2) the name of the formula argument is FUN or (3) the formula argument is not the first argument in the argument list.

Usage

"$.fn"(x, FUN)

Arguments

x

fn.

FUN

Name of a function.

Value

• Returns a function.

See Also

as.function.formula

Examples

# use of formula to specify a function.
   # Note that LETTERS, letters and pi are automatically excluded from args
   fn$lapply(list(1:4, 1:3), ~ LETTERS[x])
   fn$sapply(1:3, ~ sin((n-1):n * pi/180))

   # use of simplify = rbind instead of do.call(rbind, by(...)).
   # args to anonymous function are automatically determined.
   fn$by(BOD, 1:nrow(BOD), ~ c(mn = min(x), mx = max(x)), simplify = rbind)

   # calculate lm coefs of uptake vs conc for each Plant
   fn$by(CO2, CO2$Plant, d ~ coef(lm(uptake ~ conc, d)), simplify = rbind)

   # mid range of conc and uptake by Plant
   fn$aggregate(CO2[,4:5], CO2[1], ~ mean(range(x)))

# same but use cast/melt from reshape package
   library(reshape)
   fn$cast(Plant ~ variable, data = melt(CO2, id = 1:3), ~ mean(range(x)))

   # same
   # uncomment when new version of doBy comes out (expected shortly)
   # library(doBy)
   # fn$summaryBy(.~Plant,CO2[-(2:3)],FUN=~mean(range(x)), pref='midrange')

   # generalized matrix product
   # can replace sum(x*y) with any other inner product of interest
   # this example just performs matrix multiplication of a times b
   a <- matrix(4:1, 2)
   b <- matrix(1:4, 2)
   fn$apply(b, 2, x ~ fn$apply(a, 1, y ~ sum(x*y)))

   # integration
   fn$integrate(~1/((x+1)*sqrt(x)), lower = 0, upper = Inf)

   # optimization
   fn$optimize(~ x^2, c(-1,1))

   # using fn with S4 definitions
   setClass('ooc', representation(a = 'numeric'))
   fn$setGeneric('incr', x + value ~ standardGeneric('incr'))
   fn$setMethod('incr', 'ooc', x + value ~ {x@a <- x@a+value; x})
   oo <- new('ooc',a=1)
   oo <- incr(oo,1)
   oo

# plot quantile regression fits for various values of tau
   library(quantreg)
   data(engel)
   plot(engel$x, engel$y, xlab = 'income', ylab = 'food expenditure')
   junk <- fn$lapply(1:9/10, tau ~ abline(coef(rq(y ~ x, tau, engel))))

   # rolling mid-range
   library(zoo)
   fn$rollapply(LakeHuron, 12, ~ mean(range(x)))

   library(lattice)
   fn$xyplot(uptake ~ conc | Plant, CO2,
      panel = ... ~ { panel.xyplot(...); panel.text(200, 40, lab = 'X') })

   library(boot)
   set.seed(1)
   fn$boot(rivers, ~ median(x, d), R = 2000)

   x <- 0:50/50
   matplot(x, fn$outer(x, 1:8, ~ sin(x * k*pi)), type = 'blobcsSh')