Apply a Function to Multiple Arrays with Implicit Expansion

Source: R/implicitExpansion.R

Similar function to mapply with support for implicit expansion.

mmapply(
  FUN,
  ...,
  MoreArgs = list(),
  SIMPLIFY = TRUE,
  USE.NAMES = TRUE,
  ALLOW.RECYCLING = FALSE
)

Arguments

FUN

Function to apply to each combination of arguments. Found via match.fun.

...

Objects that are coerced to arrays, expanded using implicit expansion, and then vectorized over.

MoreArgs

Pass arguments in a list instead of ...

SIMPLIFY

If TRUE, the resulting list array is simplified to an atomic array if possible.

USE.NAMES

If TRUE, the dimensions are named using the names of input arguments of matching size.

ALLOW.RECYCLING

Whether to allow recycling of elements in each dimension.

Value

An array containing the result of FUN for each combination of entries from ... after implicit expansion.

Details

Most arguments are handled in a similar fashion to mapply with some key differences:

  • Entries of MoreArgs are treated the same as the ones in ..., i.e. mmapply(...) is the same as mmapply(MoreArgs = list(...)). Additional arguments to FUN can be passed here or in ..., either as they are (if they are atomic), or as a list() of length one.

  • SIMPLIFY only simplifies a list array to an atomic array, nothing else.

  • USE.NAMES uses names from all arguments, but never uses an argument itself as names.

If ALLOW.RECYCLING is set to TRUE, all arrays of any size are compatible.

Examples

summaries <- list(Max = max, Min = min, avg = mean)
data <- list(a = 1:5, b = 2:3, c = 20:12)
formatStrings <- array(c('%.1f', '%.3f'), c(1,1,2))
mmapply(function(f, d, s) sprintf(s, f(d)), summaries, t(data), formatStrings)
#> , , 1
#> 
#>     a     b     c     
#> Max "5.0" "3.0" "20.0"
#> Min "1.0" "2.0" "12.0"
#> avg "3.0" "2.5" "16.0"
#> 
#> , , 2
#> 
#>     a       b       c       
#> Max "5.000" "3.000" "20.000"
#> Min "1.000" "2.000" "12.000"
#> avg "3.000" "2.500" "16.000"
#>